cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.22033/esgf/cmip6.5700
title: MIROC MIROC6 model output prepared for CMIP6 RFMIP piClim-histaer

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.RFMIP.MIROC.MIROC6.piClim-histaer' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'.
 
 The MIROC6 climate model, released in 2017, includes the following components:
 aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T85; 256 x 128 longitude/latitude; 81 levels; top level 0.004 hPa), land: MATSIRO6.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), seaIce: COCO4.9. 
The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km. 

Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.22033/esgf/cmip6.5704
title: MIROC MIROC6 model output prepared for CMIP6 RFMIP piClim-lu

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.RFMIP.MIROC.MIROC6.piClim-lu' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'.
 
 The MIROC6 climate model, released in 2017, includes the following components:
 aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T85; 256 x 128 longitude/latitude; 81 levels; top level 0.004 hPa), land: MATSIRO6.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), seaIce: COCO4.9. 
The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km. 

Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.5281/zenodo.15545301
title: Date primare PN0201

description: Set date primare profile plaja din expeditia Plaje Perisor Periboina in locatia Portita - iulie 2021
DOI: 10.5281/zenodo.15545302
title: Date primare PN0201

description: Set date primare profile plaja din expeditia Plaje Perisor Periboina in locatia Portita - iulie 2021
DOI: 10.5281/zenodo.15319014
title: Metal bottlenecks along energy transitions call for technology flexibility and sobriety

description: In the "Data" folder, you’ll find all necessary data to run the "IAM_Techno_Optimisation.py" script, available on GitHub (https://github.com/Pelotte/iam-metal-demand-optimizer/tree/master).

The "IAM_Techno_Optimisation.py" script is a tool designed to:



Quantify metal supply and demand by sector through 2050, using energy and transport projections from various IAMs and SSP-RCP scenarios.

Optimize the IAM technological mix, minimizing adjustments needed to prevent metal demand from exceeding supply constraints.


This tool supports all IAMs with power projections for SSP-RCP scenarios provided in the IPCC’s Sixth Assessment Report (AR6), Working Group III, and available in the IIASA SSP database, but SSP3 has been excluded since it does not align with the scope of our study.

Data for RCP 2.6, SSPs 1, 2, 4, 5, of the SSP marker IAM models of the IPCC, are organized in the "Capacity Factor IAM," "GDP IAM," "Population IAM", "Transport IAM" and "Power Capacity IAM" folders. See the GitHub README for more details.
DOI: 10.5281/zenodo.15319015
title: Metal bottlenecks along energy transitions call for technology flexibility and sobriety

description: In the "Data" folder, you’ll find all necessary data to run the "IAM_Techno_Optimisation.py" script, available on GitHub (https://github.com/Pelotte/iam-metal-demand-optimizer/tree/master).

The "IAM_Techno_Optimisation.py" script is a tool designed to:



Quantify metal supply and demand by sector through 2050, using energy and transport projections from various IAMs and SSP-RCP scenarios.

Optimize the IAM technological mix, minimizing adjustments needed to prevent metal demand from exceeding supply constraints.


This tool supports all IAMs with power projections for SSP-RCP scenarios provided in the IPCC’s Sixth Assessment Report (AR6), Working Group III, and available in the IIASA SSP database, but SSP3 has been excluded since it does not align with the scope of our study.

Data for RCP 2.6, SSPs 1, 2, 4, 5, of the SSP marker IAM models of the IPCC, are organized in the "Capacity Factor IAM," "GDP IAM," "Population IAM", "Transport IAM" and "Power Capacity IAM" folders. See the GitHub README for more details.
DOI: 10.5281/zenodo.15545201
title: Data from: Seagrass Species Identity Drives Leaf Litter Decomposition Across a Naturally Occurring Phosphorus Gradient

description: Decomposition is one of several controls on carbon storage in seagrass meadows, but the relative importance of environmental conditions and seagrass species identity in driving decomposition is unclear. We first investigated direct environmental effects on decomposition by measuring percent mass lost of standardized litter, green and rooibos (red) tea, incubated in meadows spanning a naturally occurring phosphorus gradient for up to 2 years; we then investigated indirect effects by measuring percent mass lost of seagrass leaf litter sourced from these meadows and incubated in a single location for up to 2 months. We tested the effect of species identity on decomposition by incubating litter from two seagrass species, the larger-bodied Thalassia testudinum and the smaller-bodied Halodule wrightii. We found evidence for both direct and indirect environmental effects on decomposition: the green tea decay rate was lowest at the phosphorus-limited site (0.011 d−1), and T. testudinum litter decay rate was lowest for leaves collected from the phosphorus-limited site (0.017 d−1). Species identity had a stronger effect on leaf litter decomposition, where mean leaf litter decay rates were consistently greater for T. testudinum (k = 0.022 ± 0.002 SE) compared to H. wrightii (k = 0.010 ± 0.001 SE). This finding was unexpected because T. testudinum meadows are typically associated with higher sediment carbon stocks than meadows dominated by other species and suggests that T. testudinum may promote carbon storage by producing above- and belowground litter in quantities that accrue as sediment carbon despite fast initial leaf litter decay rates, or through other mechanisms, such as particle trapping by the seagrass canopy.
description: Data are provided in separate .csv files, each with accompanying metadata files. GPS coordinates for site locations are included in the supplementary material associated with the published journal article.
DOI: 10.5281/zenodo.15545202
title: Data from: Seagrass Species Identity Drives Leaf Litter Decomposition Across a Naturally Occurring Phosphorus Gradient

description: Decomposition is one of several controls on carbon storage in seagrass meadows, but the relative importance of environmental conditions and seagrass species identity in driving decomposition is unclear. We first investigated direct environmental effects on decomposition by measuring percent mass lost of standardized litter, green and rooibos (red) tea, incubated in meadows spanning a naturally occurring phosphorus gradient for up to 2 years; we then investigated indirect effects by measuring percent mass lost of seagrass leaf litter sourced from these meadows and incubated in a single location for up to 2 months. We tested the effect of species identity on decomposition by incubating litter from two seagrass species, the larger-bodied Thalassia testudinum and the smaller-bodied Halodule wrightii. We found evidence for both direct and indirect environmental effects on decomposition: the green tea decay rate was lowest at the phosphorus-limited site (0.011 d−1), and T. testudinum litter decay rate was lowest for leaves collected from the phosphorus-limited site (0.017 d−1). Species identity had a stronger effect on leaf litter decomposition, where mean leaf litter decay rates were consistently greater for T. testudinum (k = 0.022 ± 0.002 SE) compared to H. wrightii (k = 0.010 ± 0.001 SE). This finding was unexpected because T. testudinum meadows are typically associated with higher sediment carbon stocks than meadows dominated by other species and suggests that T. testudinum may promote carbon storage by producing above- and belowground litter in quantities that accrue as sediment carbon despite fast initial leaf litter decay rates, or through other mechanisms, such as particle trapping by the seagrass canopy.
description: Data are provided in separate .csv files, each with accompanying metadata files. GPS coordinates for site locations are included in the supplementary material associated with the published journal article.
DOI: 10.15468/dl.skybhr
title: Occurrence Download

description: A dataset containing 115 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Rhododendron araiophyllum Balf.fil. & W.W.Sm."
 ]
}

 The dataset includes 115 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000878-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14226699
title: MTN deficient scRNA-seq

description: "3KR" refers to scRNA-seq data from the intestinal tissues of mice fed a methionine-, tryptophan-, and niacin-deficient diet followed by recovery on a regular diet."3K" refers to scRNA-seq data from the intestines of mice continuously fed a methionine-, tryptophan-, and niacin-deficient diet."REG" represents scRNA-seq data from the intestinal tissues of mice maintained on a regular diet.The file mouse_combined.rds contains the integrated dataset of these three conditions, processed using Seurat.
DOI: 10.5281/zenodo.14226700
title: MTN deficient scRNA-seq

description: "3KR" refers to scRNA-seq data from the intestinal tissues of mice fed a methionine-, tryptophan-, and niacin-deficient diet followed by recovery on a regular diet."3K" refers to scRNA-seq data from the intestines of mice continuously fed a methionine-, tryptophan-, and niacin-deficient diet."REG" represents scRNA-seq data from the intestinal tissues of mice maintained on a regular diet.The file mouse_combined.rds contains the integrated dataset of these three conditions, processed using Seurat.
DOI: 10.15468/dl.sdvbbz
title: Occurrence Download

description: A dataset containing 111 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Rhododendron ×agastum Balf.fil. & W.W.Sm."
 ]
}

 The dataset includes 111 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000879-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9aaj38
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((100.327 1.828181, 100.256702 1.822613, 100.188135 1.806045, 100.122991 1.778887, 100.062872 1.741806, 100.009261 1.695718, 99.963477 1.641756, 99.926647 1.581251, 99.89967799999999 1.515692, 99.88323200000001 1.446695, 99.877714 1.375957, 99.883258 1.305222, 99.899727 1.236231, 99.926715 1.170681, 99.96355699999999 1.110188, 100.009346 1.056239, 100.062953 1.010163, 100.123059 0.973094, 100.188185 0.945945, 100.256728 0.929383, 100.327 0.923817, 100.397272 0.929383, 100.465815 0.945945, 100.530941 0.973094, 100.591047 1.010163, 100.644654 1.056239, 100.690443 1.110188, 100.727285 1.170681, 100.754273 1.236231, 100.770742 1.305222, 100.776286 1.375957, 100.770768 1.446695, 100.754322 1.515692, 100.727353 1.581251, 100.690523 1.641756, 100.644739 1.695718, 100.591128 1.741806, 100.531009 1.778887, 100.465865 1.806045, 100.397298 1.822613, 100.327 1.828181))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020852-260108223611665/datasets/export for details.
DOI: 10.15468/dl.qkh63r
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Esox lucius",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1855",
 "Year is less than or equal to 1859"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020851-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zj9qfz
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((99.666 9.699062, 99.59472599999999 9.693489, 99.52521400000001 9.676909, 99.459181 9.64973, 99.398259 9.612625, 99.34395000000001 9.566511, 99.29759199999999 9.512525999999999, 99.260327 9.452002, 99.23306700000001 9.386434, 99.21648 9.317437, 99.21096799999999 9.246712, 99.21666 9.176, 99.23340899999999 9.107043000000001, 99.260797 9.041537, 99.29814500000001 8.981093, 99.344531 8.927194999999999, 99.39881099999999 8.881168000000001, 99.45965099999999 8.844142, 99.525555 8.817026, 99.594905 8.800485999999999, 99.666 8.794926999999999, 99.737095 8.800485999999999, 99.806445 8.817026, 99.872349 8.844142, 99.933189 8.881168000000001, 99.987469 8.927194999999999, 100.033855 8.981093, 100.071203 9.041537, 100.098591 9.107043000000001, 100.11534 9.176, 100.121032 9.246712, 100.11552 9.317437, 100.098933 9.386434, 100.071673 9.452002, 100.034408 9.512525999999999, 99.98805 9.566511, 99.933741 9.612625, 99.87281900000001 9.64973, 99.806786 9.676909, 99.737274 9.693489, 99.666 9.699062))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 64 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020850-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18302162
title: Psidium salutare var. mucronatum Landrum. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.5281/zenodo.18302161
title: Psidium salutare var. mucronatum Landrum. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.15468/dl.xszpzx
title: Occurrence Download

description: A dataset containing 683 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leersia japonica"
 ]
}

 The dataset includes 683 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020853-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2q5zmb
title: Occurrence Download

description: A dataset listing the 37 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Catálogo de cangrejos anomuros y braquiuros de las lagunas costeras de mayor extensión en el litoral mexicano del Golfo de México"
 ]
}

 The dataset's 37 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020842-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18302178
title: Psidium salutare var. sericeum (Cambess.) Landrum. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.5281/zenodo.18302179
title: Psidium salutare var. sericeum (Cambess.) Landrum. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.15468/dl.jhug3m
title: Occurrence Download

description: A dataset containing 544 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Curculio sikkimensis"
 ]
}

 The dataset includes 544 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020854-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18301594
title: Sample Dataset for AI-Generated Scientific Storytelling

description: This repository contains the dataset used to fine-tune an AI Scientific Storyteller .

The released data represents the training material and is provided to illustrate the structure, format, and intermediate representations used in the scientific storytelling pipeline.

Contents:



new_dataset.json: metadata describing scientific papers and associated narrative sources.

new_parsed_output.json: parsed text of scientific papers used as model input.

new_stories_with_text.json: narrative texts used as supervision for story generation.
DOI: 10.5281/zenodo.18301593
title: Sample Dataset for AI-Generated Scientific Storytelling

description: This repository contains the dataset used to fine-tune an AI Scientific Storyteller .

The released data represents the training material and is provided to illustrate the structure, format, and intermediate representations used in the scientific storytelling pipeline.

Contents:



new_dataset.json: metadata describing scientific papers and associated narrative sources.

new_parsed_output.json: parsed text of scientific papers used as model input.

new_stories_with_text.json: narrative texts used as supervision for story generation.
DOI: 10.23687/b8c6fcfb-f13f-45c1-84fe-039da0e238a8
title: Longevity and fecundity of females from six Trichogramma species depending on the access to hosts and food
title: Longévité et fécondité de femelles de six espèces de trichogrammes selon l’accès aux hôtes et à la nourriture

description: In this study, we investigated the impact of different food sources on life-history traits, such as longevity and fecundity, in females egg parasitoids of six Trichogramma species (two thelytokous and four arrhenotokous): T. cacoeciae Marchal, T. chilonis Ishii, T. minutum Riley, T. leptoparameron Dyurich, T. pintoi Voegele and T. sibericum Sorokina (Hymenoptera: Trichogrammatidae). Five treatments were tested: control (no food, no host), sugar (provided as honey), sugar and hosts, hosts. Hosts were provided as eggs of Ephestia kuehniella. Females were either dissected and oocytes were count at emergence, at death or at different time during their life.
description: Dans cette étude, nous avons examiné l'impact de différentes sources alimentaires sur les traits d’histoire de vie, telles que la longévité et la fécondité, chez les femelles parasitoïdes de six espèces de Trichogramma (deux thélytoques et quatre arrhénotoques) : T. cacoeciae Marchal, T. chilonis Ishii, T. minutum Riley, T. leptoparameron Dyurich, T. pintoi Voegele et T. sibericum Sorokina (Hymenoptera : Trichogrammatidae). Cinq traitements ont été testés : témoin (sans nourriture, sans hôte), sucre (fourni sous forme de miel), sucre et hôtes, hôtes. Les hôtes ont été fournis sous forme d'œufs d'Ephestia kuehniella. Les femelles ont été disséquées et les oocytes ont été comptés à l'émergence, à la mort ou à différents moments de leur vie.