cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14886977
title: Conservation outcomes of dietary transitions across different values of nature - model outputs

description: Archive of output reports produced for the MAgPIE v4.8.2 paper Conservation outcomes of dietary transitions across different values of nature.

Data

The data contain the MAgPIE model and post-processing outputs for all assessed scenarios, including the sensitivity test across the SSP1 and SSP3 scenarios.



The file rev9_healthyLscps_AOH_full_report.Rds contains the outputs of our Area of Habitat (AOH) assessment for all assessed species and across all scenarios. The summary statistics shown in Figure 2 and Figure 3 have been derived from this data set. The data has also been used to create Extended Data Figures 5-7 and is shown in the Supplementary Information. However, for Extended Data Figure 7 the data was used in combination with rasterized range polygons obtained from the IUCN Red List Database (IUCN 2020).

The file rev9_healthyLscps_pollSuff_report_all.Rds reports the global and regional cropland area (Mha) that is subject to insufficient and sufficient pollination supply. This is specified in the column ‘poll_class’, where 1 is insufficient and 2 is sufficient pollination supply. The data is shown in Figure 4, Extended Data Figure 8 and the Supplementary Information.

The file rev9_healthyLscps_RUSLE_report_all.Rds  reports estimated global and regional soil loss in Pg per year across all modelled scenarios. The data is displayed in Figure 4, Extended Data Figure 9 and the Supplementary Information.

The file rev9_healthyLscps_allSSP_report.rds contains regional and global output variables from the MAgPIE model used in this study. The data is shown in Figure 1 and 5, as well as in Extended Data Figures 2-4 and the Supplementary Information.

The file rev9_healthyLscps_validation.rds contains validation data for the MAgPIE model output variables.


 

Model code

The model code of the MAgPIE and SEALS models can be accessed via:

MAgPIE model code:



https://doi.org/10.5281/zenodo.13833444 and https://github.com/magpiemodel/magpie


MAgPIE model documentation:



https://rse.pik-potsdam.de/doc/magpie/4.8.2/


SEALS model code:



https://github.com/jandrewjohnson/seals_dev/releases/tag/v1.0.0


SEALS mode documentation:



https://justinandrewjohnson.com/earth_economy_devstack/seals_overview.html


 

Cited references

IUCN. (2020). The IUCN Red List of Threatened Species. Version 2020-2. https://www.iucnredlist.org. Downloaded on 25 November 2020
DOI: 10.13144/lil-1165
title: Recensement de la population 2014 : fichier détail migrations résidentielles des individus entre commune de résidence actuelle et pays de résidence antérieure

description: Le fichier détail  du recensement de la population de 2014 "Migrations résidentielles des individus entre commune de résidence actuelle et pays de résidence antérieure" est de nouveau diffusé après quatre ans de suspension (entre 2009 et 2012) suite à un changement de questionnaire. Ce fichier détail fait désormais référence à la résidence antérieure des personnes recensées 1 an avant leur interrogation (contre 5 ans pour les recensements de la population 2006, 2007 et 2008).  Il porte sur la résidence actuelle et antérieure des individus, leurs principales caractéristiques sociodémographiques, ainsi que celles du ménage auquel ils appartiennent. Les variables y sont disponibles avec des modalités détaillées, y compris les variables à diffusion restreinte (nationalité, pays de naissance, ancienneté d'arrivée en France). A partir de ce fichier, il est donc possible de faire des analyses exploratoires de données, de modéliser des comportements, ou simplement de tabuler sur une sous-population particulière définie selon certains critères : appartenance à une zone géographique et/ou unité statistique présentant certaines caractéristiques.
DOI: 10.15468/dl.wcrmxc
title: Occurrence Download

description: A dataset containing 2760 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Diplodus cervinus (Lowe, 1838)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen, Material sample)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 2760 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004347-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29224448.v4
title: <b>Code availability</b> for the article "<b>Single-shot full-Stokes imaging through scattering media</b>"

description: Post-publication updates：1.A README file has been added to enhance usability and improve the overall user experience of the open-source release.2.The dataset for Fig. 4 and Visualization are too large to upload in full. Here we provide only the test set corresponding to Fig. 4, along with the trained weight files, to facilitate verification and reproduction.If you would like to obtain the complete version of the dataset, please state your purpose, provide proof that it will be used solely for academic and other non-commercial purposes, complete the application form, <b>and contact the authors at </b><b><i>renxs@bupt.cn</i></b>. In addition, any potential publications resulting from the use of the dataset must cite the following reference in one of the formats below:<b>APA 7</b><br>Ren, X., Tian, Y., Ren, Y., Wang, B., Zhang, S., et al. (2025). Single-shot full-Stokes imaging through scattering media. <i>Optica, 12</i>(10), 1560–1568.<b>IEEE</b><br>X. Ren <i>et al.</i>, “Single-shot full-Stokes imaging through scattering media,” <i>Optica</i>, vol. 12, no. 10, pp. 1560–1568, Sep. 2025, doi: 10.1364/OPTICA.572713.<b>Chicago (Author–Date)</b><br>Ren, Xiansong, Ye Tian, Yanling Ren, Bo Wang, Shifeng Zhang, et al. 2025. “Single-shot Full-Stokes Imaging through Scattering Media.” <i>Optica</i> 12 (10): 1560–1568.
DOI: 10.6084/m9.figshare.29224448.v3
title: <b>Code availability</b> for the article "<b>Single-shot full-Stokes imaging through scattering media</b>"

description: The dataset for Fig. 4 and Video 1 is too large to upload in full. Here we provide only the test set corresponding to Fig. 4, along with the trained weight files, to facilitate verification and reproduction. For access to the complete dataset, please contact renxs@bupt.cn and it will be provided within 24 hours. or search for <code>dataset_opticafig4.zip</code> on the Featurize cloud computing platform; I have already made it publicly available.
DOI: 10.15468/dl.9um8ny
title: Occurrence Download

description: A dataset containing 22893 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Curruca cantillans)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 22893 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014570-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qzfndn
title: Occurrence Download

description: A dataset containing 449 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Anemone hupehensis japonica)"
 ]
}

 The dataset includes 449 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014571-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.763mh5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Elaeagnus multiflora",
 "Country is Libya",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014572-250920141307145/datasets/export for details.
DOI: 10.34740/kaggle/dsv/13165023
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.ysbdqa
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Elaeagnus multiflora",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 27 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014573-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5unfhj
title: Occurrence Download

description: A dataset containing 213 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is greater than or equal to 2000",
 "CoordinateUncertaintyInMeters is less than 300",
 "TaxonKey is Loasa tricolor"
 ]
}

 The dataset includes 213 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014575-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17195468
title: Annotated Forestry Images Dataset With Trees and Boulders

description: This dataset is divided into a training part and an evaluation part. It contains forest images along with annotations in YOLO and COCO formats.
DOI: 10.5281/zenodo.17195469
title: Annotated Forestry Images Dataset With Trees and Boulders

description: This dataset is divided into a training part and an evaluation part. It contains forest images along with annotations in YOLO and COCO formats.
DOI: 10.5281/zenodo.17197511
title: COVID-19-Hospitalisierungen in Deutschland

description: Im Datensatz "COVID-19-Hospitalisierungen in Deutschland" des Robert Koch-Institutswerden täglich aktualisierte Informationen zu Hospitalisierungen im Zusammenhang mit COVID-19 basierend auf den Meldungen nach dem Infektionsschutzgesetz (IfSG) bereitgestellt. Neben tagesaktuellen Fallzahlen und Inzidenzen auf Bundes- und Länderebene enthält der Datensatz auch modellgestützte Schätzungen verzögert gemeldeter Hospitalisierungen mittels Nowcasting. Ziel ist es, die tatsächliche Belastung des Gesundheitssystems durch COVID-19 besser abzubilden, insbesondere durch die Berechnung adjustierter 7-Tage-Hospitalisierungsinzidenzen.
DOI: 10.15468/dl.ymrt85
title: Occurrence Download

description: A dataset containing 32661174 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Chinese Taipei, Hong Kong)",
 "Year 1950-2023"
 ]
}

 The dataset includes 32661174 records from 4775 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014521-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0176862.10fu
title: SH0176862.10FU

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/sh0176863.10fu
title: SH0176863.10FU

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: 10.18150/mahni8
title: Bifunctional silk nanospheres for targeted delivery of oligonucleotide therapeutics to VEGFR-positive cells in the tumor microenvironment

description: This dataset contains experimental data supporting the publication “Bifunctional silk nanospheres for targeted delivery of oligonucleotide therapeutics to VEGFR-positive cells in the tumor microenvironment.” The study was conducted as part of a research project funded by the National Science Centre (grant no. 2021/43/D/NZ7/00622).The purpose of the study was to develop and evaluate a targeted drug delivery system based on functionalized silk nanospheres for the selective delivery of oligonucleotide therapeutics to vascular endothelial growth factor receptor (VEGFR)-overexpressing cells in the tumor microenvironment.The dataset includes data generated during the engineering and characterization of five hybrid silk proteins produced by fusing bioengineered MS1 silk with peptides targeting VEGFR-1 (VE1MS1, VE1bMS1, VE1cMS1) and VEGFR-2 (VE2bMS1, VE2cMS1). These constructs were assessed for receptor binding and cellular internalization in VEGFR-overexpressing cells, resulting in the selection of VE1MS1 and VE2bMS1 as lead candidates for drug delivery system development.Further data document the formation of bifunctional silk nanospheres obtained by blending VE1MS1 or VE2bMS1 with the nucleic acid–binding silk protein MS2KN. The dataset covers nanoparticle physicochemical characterization, nucleic acid-binding capacity, cytotoxicity, cellular uptake, selective interaction with VEGFR-overexpressing non-small-cell lung cancer cells, and therapeutic efficacy, including siRNA-mediated gene silencing.The dataset provides comprehensive experimental evidence demonstrating that incorporation of VEGFR-targeting enhances receptor-specific cellular interactions, and, in combination with MS2KN, enables efficient and targeted delivery of siRNA therapeutics to the VEGFR-overexpressing cells of the tumor microenvironment.
DOI: 10.15156/bio/sh0176864.10fu
title: SH0176864.10FU

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/sh0176865.10fu
title: SH0176865.10FU

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/sh0176866.10fu
title: SH0176866.10FU

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/sh0176867.10fu
title: SH0176867.10FU

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: 10.3886/e239711v2
title: Virtual Reality

description: Youming Zhang, School of Physical Education and Health Science, Mudanjiang Normal University, Mudanjiang, Heilongjiang Province, China<br>
DOI: 10.15156/bio/sh0176868.10fu
title: SH0176868.10FU

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/sh0176869.10fu
title: SH0176869.10FU

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/sh0176870.10fu
title: SH0176870.10FU

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.