cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.d89fzs
title: Occurrence Download

description: A dataset containing 5644 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Afghanistan",
 "DatasetKey is NMNH Extant Specimen Records (USNM, US)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 5644 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002046-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8psvvq
title: Occurrence Download

description: A dataset containing 4240 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Afghanistan",
 "DatasetKey is EURISCO, The European Genetic Resources Search Catalogue",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 4240 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002047-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vfy53w
title: Occurrence Download

description: A dataset containing 3467 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Afghanistan",
 "DatasetKey is United States National Plant Germplasm System Collection",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3467 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002048-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.72c8zd
title: Occurrence Download

description: A dataset containing 3398 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Afghanistan",
 "DatasetKey is Natural History Museum, Vienna - Herbarium W",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3398 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002049-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dp2wtj
title: Occurrence Download

description: A dataset containing 21430 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (USA.36.18_1, USA.36.78_1)",
 "TaxonKey is Hymenoptera"
 ]
}

 The dataset includes 21430 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002050-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qfx3ek
title: Occurrence Download

description: A dataset containing 348 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Stellaria dichotoma L."
 ]
}

 The dataset includes 348 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002051-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.up4vt7
title: Occurrence Download

description: A dataset containing 263 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ferula bungeana Kitag."
 ]
}

 The dataset includes 263 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002052-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nru4bu
title: Occurrence Download

description: A dataset containing 1127 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sphallerocarpus gracilis (Besser ex Trevis.) Koso-Pol."
 ]
}

 The dataset includes 1127 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002053-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g433c9
title: Occurrence Download

description: A dataset containing 492 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Polygonum divaricatum Less."
 ]
}

 The dataset includes 492 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002054-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14879104
title: MESA and Python files for "Enabling high mass accretion rates onto massive main sequence stars by outer envelope mass removal"

description: This upload contains a MESA model for an 80 solar mass star that undergoes mass accretion without expanding in radius. The process is done through repeated simulation pulses, each consisting of two steps:

1. Mass and energy accretion (using accretion_inlist) until the radius reaches a set limit.2. Mass removal (using reduction_inlist) to bring the star back to its original radius.

By running multiple pulses, the star can accrete up to ~10% of its initial mass without expanding, as shown in the paper:

Enabling high mass accretion rates onto massive main sequence stars by outer envelope mass removal - Ariel Scolnic, Ealeal Bear, and Noam Soker (2025)

---Inside the provided `.zip` file, you'll find:

1. A starting folder containing the initial MESA model.2. auto_runner.py – A Python script to automate the simulation process.3. accretion_inlist – The inlist for the accretion phase of each pulse.4. reduction_inlist – The inlist for the mass removal phase.

Recommended folder structure before running the script:

main_directory/├── auto_runner.py├── starting_folder/│   ├── LOGS/                 # Latest logs to continue simulations from│   ├── model.mod             # The corresponding .mod file│   ├── accretion_inlist      # Inlist for the accretion phase│   ├── reduction_inlist      # Inlist for the reduction phase

---

To start the simulations, first, create a new main folder and place auto_runner.py along with the starting folder inside. The starting folder should contain the latest LOGS directory, the corresponding .mod file, and accretion_inlist and reduction_inlist files. Open a terminal in the main folder. Run the script by entering python3.11 auto_runner.py and follow the prompts. If continuing from a previous run, confirm when asked. If multiple folders are present, select the correct one to resume from. If the chosen folder contains multiple .mod files, choose the appropriate one. Finally, specify the number of pulses (N) to run. Since each pulse consists of two steps, the script will generate 2N new folders.

---Notes

1. The accretion and reduction phases are structured to keep the star within a set radius.2. If continuing a simulation, ensure the latest `LOGS` folder and `.mod` file are present.3. The script automatically manages folders, creating new ones for each pulse.4. I used MESA version 24.03.1, with SDK version 23.7.3 (Linux, x86_64)
DOI: 10.5281/zenodo.14879105
title: MESA and Python files for "Enabling high mass accretion rates onto massive main sequence stars by outer envelope mass removal"

description: This upload contains a MESA model for an 80 solar mass star that undergoes mass accretion without expanding in radius. The process is done through repeated simulation pulses, each consisting of two steps:

1. Mass and energy accretion (using accretion_inlist) until the radius reaches a set limit.2. Mass removal (using reduction_inlist) to bring the star back to its original radius.

By running multiple pulses, the star can accrete up to ~10% of its initial mass without expanding, as shown in the paper:

Enabling high mass accretion rates onto massive main sequence stars by outer envelope mass removal - Ariel Scolnic, Ealeal Bear, and Noam Soker (2025)

---Inside the provided `.zip` file, you'll find:

1. A starting folder containing the initial MESA model.2. auto_runner.py – A Python script to automate the simulation process.3. accretion_inlist – The inlist for the accretion phase of each pulse.4. reduction_inlist – The inlist for the mass removal phase.

Recommended folder structure before running the script:

main_directory/├── auto_runner.py├── starting_folder/│   ├── LOGS/                 # Latest logs to continue simulations from│   ├── model.mod             # The corresponding .mod file│   ├── accretion_inlist      # Inlist for the accretion phase│   ├── reduction_inlist      # Inlist for the reduction phase

---

To start the simulations, first, create a new main folder and place auto_runner.py along with the starting folder inside. The starting folder should contain the latest LOGS directory, the corresponding .mod file, and accretion_inlist and reduction_inlist files. Open a terminal in the main folder. Run the script by entering python3.11 auto_runner.py and follow the prompts. If continuing from a previous run, confirm when asked. If multiple folders are present, select the correct one to resume from. If the chosen folder contains multiple .mod files, choose the appropriate one. Finally, specify the number of pulses (N) to run. Since each pulse consists of two steps, the script will generate 2N new folders.

---Notes

1. The accretion and reduction phases are structured to keep the star within a set radius.2. If continuing a simulation, ensure the latest `LOGS` folder and `.mod` file are present.3. The script automatically manages folders, creating new ones for each pulse.4. I used MESA version 24.03.1, with SDK version 23.7.3 (Linux, x86_64)
DOI: 10.5281/zenodo.14879526
title: POPC aux replicate 3

description: Parameterized with Sage2.2.1-aux TIP3P water parameters

 

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.5281/zenodo.14879527
title: POPC aux replicate 3

description: Parameterized with Sage2.2.1-aux TIP3P water parameters

 

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.21227/6vsa-1d19
title: S D International

description: S D International is a leading dyes & chemicals manufacturer and Supplier with ISO 9001:2015 Certified who offers a vast portfolio of Colorants to our customers across the globe. More than a decade in product development and innovation for the textile industry, our products mainly go into the multiple sectors including the Wood, Paper, Printing Inks, Paints, Coatings, Plastics, Rubber, Food Industry and packaging industries. We supply and export our products in more than 50 countries across the globe. Our key service divisions assist brands and their industry partners from their first inspiration throughout the entire supply chain to ensure that they meet utmost quality and ecological specifications which lead to reduced cost and shorten lead times. We offer state-of-the-art colour communication through CSI; textile and ecology testing through Texanlab; ecology and environmental advice, supply chain auditing and consulting for RSL compliant sustainable processes. S D International gives assurance to all our customers that the Products supplied by us are with legal requirements. We also provide expertise so that selected products are compliant with voluntary Restricted Substances Lists (RSLs), including those of brands and Industry Partners. We always support long-term partnerships along the supply chain to all our customers.
DOI: 10.5281/zenodo.14879323
title: E.coli single molecule RNA FISH data
DOI: 10.5281/zenodo.14879324
title: E.coli single molecule RNA FISH data
DOI: 10.5281/zenodo.14879560
title: POPC Sage2.2.0 replicate 1

description: Parameterized with OpenFF sage2.2.0

 

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.5281/zenodo.14879561
title: POPC Sage2.2.0 replicate 1

description: Parameterized with OpenFF sage2.2.0

 

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.5281/zenodo.14867657
title: POPC openff-1.3.1 replicate 1

description: Parameterized with OpenFF openff-1.3.1.offxml, AM1BCC charges, TIP3P water parameters

 

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.5281/zenodo.14867658
title: POPC openff-1.3.1 replicate 1

description: Parameterized with OpenFF openff-1.3.1.offxml, AM1BCC charges, TIP3P water parameters

 

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.5281/zenodo.14713792
title: POPC aux replicate 1

description: POPC simulation parameterized with Sage2.2.1.aux.offxml

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.5281/zenodo.14713793
title: POPC aux replicate 1

description: POPC simulation parameterized with Sage2.2.1.aux.offxml

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.5281/zenodo.14713771
title: POPC core replicate 1

description: POPC simulation parameterized with Sage2.2.1.core.offxml

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.5281/zenodo.14713770
title: POPC core replicate 1

description: POPC simulation parameterized with Sage2.2.1.core.offxml

Lipids: POPCLipid count: 128 (64 per leaflet)Solvent: TIP3PSolvent count: 5120 (40 w/l)Ions: noIon Count: n/aTemperature: 300KLength of equilibration: 100ns (40 NVT - 60 NPT)Length of production: 500ns



HMR w/ 4fs timestep

0.9 rvdw/rcouloumb cutoff

0.8 rvdw-switch


SMILES string: [C@](COP(=O)([O-])OCC[N+](C)(C)C)([H])(OC(CCCCCCC/C=C\CCCCCCCC)=O)COC(CCCCCCCCCCCCCCC)=O
DOI: 10.15468/dl.5dsxzj
title: Occurrence Download

description: A dataset containing 18655 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Snow Entomological Museum Collection",
 "TaxonKey is Curculionidae"
 ]
}

 The dataset includes 18655 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002055-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13942407
title: Continuous (hydro-)dechlorination of aromatic chloride compounds in benzyltoluene
DOI: 10.5281/zenodo.13942408
title: Continuous (hydro-)dechlorination of aromatic chloride compounds in benzyltoluene
DOI: 10.5281/zenodo.14879559
title: Continuous (hydro-)dechlorination of aromatic chloride compounds in benzyltoluene
DOI: 10.5281/zenodo.14879616
title: Population Exposure to PM
DOI: 10.5281/zenodo.14879617
title: Population Exposure to PM
DOI: 10.6084/m9.figshare.28425869
title: Tratamiento de Diabetes con células madre mesenquimales (MSC): Una revisión sistemática

description: La diabetes mellitus constituye un importante reto para la salud pública a nivel global, mostrando un aumento continuo en su incidencia. Las terapias tradicionales no han conseguido revertir la disfunción en las células β del páncreas, lo cual ha motivado la exploración de nuevas alternativas terapéuticas; en respuesta a esta situación, el propósito de esta revisión literaria fue examinar los últimos desarrollos en la aplicación de células madre mesenquimatosas (MSC) como opción de tratamiento, distinguiendo las alternativas más prometedoras a nivel internacional. <i>Metodología:</i> Se llevó a cabo una búsqueda exhaustiva en bases de datos como PubMed y Scopus, eligiendo artículos publicados en inglés durante los últimos cinco años, donde se revisaron un total de 41 artículos que satisfacían los criterios de inclusión, analizando investigaciones tanto en modelos animales como en ensayos clínicos en humanos; incluyendo estudios sobre varios tipos de MSC, en particular aquellas originadas de médula ósea (BM-MSC), tejido adiposo (ADSC), cordón umbilical (UC-MSC) y placenta. <i>Resultados:</i> Los hallazgos indicaron que las MSC cuentan con propiedades inmunomoduladoras y regenerativas, facilitando la regeneración de islotes pancreáticos, optimizando la regulación de la glucosa y disminuyendo la inflamación sistémica; sin embargo, la respuesta terapéutica difiere según la clase de MSC empleada. Después de revisar la literatura, se identificó que las células madre mesenquimatosas obtenidas del cordón umbilical (UC-MSC) son las más adecuadas para aplicaciones clínicas gracias a su alta capacidad de proliferación, baja inmunogenicidad y menor probabilidad de rechazo. <i>Conclusión:</i> Pese a los progresos realizados, la aplicación clínica de estas terapias todavía presenta obstáculos vinculados a la optimización de dosis, métodos de administración y seguridad a largo plazo, por lo que son necesarias más investigaciones para establecer protocolos estandarizados que permiten su uso seguro y efectivo en personas con diabetes.
DOI: 10.6084/m9.figshare.28425869.v1
title: Tratamiento de Diabetes con células madre mesenquimales (MSC): Una revisión sistemática

description: La diabetes mellitus constituye un importante reto para la salud pública a nivel global, mostrando un aumento continuo en su incidencia. Las terapias tradicionales no han conseguido revertir la disfunción en las células β del páncreas, lo cual ha motivado la exploración de nuevas alternativas terapéuticas; en respuesta a esta situación, el propósito de esta revisión literaria fue examinar los últimos desarrollos en la aplicación de células madre mesenquimatosas (MSC) como opción de tratamiento, distinguiendo las alternativas más prometedoras a nivel internacional. <i>Metodología:</i> Se llevó a cabo una búsqueda exhaustiva en bases de datos como PubMed y Scopus, eligiendo artículos publicados en inglés durante los últimos cinco años, donde se revisaron un total de 41 artículos que satisfacían los criterios de inclusión, analizando investigaciones tanto en modelos animales como en ensayos clínicos en humanos; incluyendo estudios sobre varios tipos de MSC, en particular aquellas originadas de médula ósea (BM-MSC), tejido adiposo (ADSC), cordón umbilical (UC-MSC) y placenta. <i>Resultados:</i> Los hallazgos indicaron que las MSC cuentan con propiedades inmunomoduladoras y regenerativas, facilitando la regeneración de islotes pancreáticos, optimizando la regulación de la glucosa y disminuyendo la inflamación sistémica; sin embargo, la respuesta terapéutica difiere según la clase de MSC empleada. Después de revisar la literatura, se identificó que las células madre mesenquimatosas obtenidas del cordón umbilical (UC-MSC) son las más adecuadas para aplicaciones clínicas gracias a su alta capacidad de proliferación, baja inmunogenicidad y menor probabilidad de rechazo. <i>Conclusión:</i> Pese a los progresos realizados, la aplicación clínica de estas terapias todavía presenta obstáculos vinculados a la optimización de dosis, métodos de administración y seguridad a largo plazo, por lo que son necesarias más investigaciones para establecer protocolos estandarizados que permiten su uso seguro y efectivo en personas con diabetes.
DOI: 10.15468/dl.veptfj
title: Occurrence Download

description: A dataset containing 571 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Catalogue of type specimens of vascular plants deposited in the Herbarium of the University of Granada (Spain)"
 ]
}

 The dataset includes 571 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002056-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yze9sz
title: Occurrence Download

description: A dataset containing 450 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((20.33325 39.2724,20.65879 39.3457,21.39178 39.47721,21.37454 39.84155,21.3616 40.19942,20.17372 40.12181,20.08317 39.57638,20.33325 39.2724))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Orchidaceae",
 "Year 2019-2025"
 ]
}

 The dataset includes 450 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002059-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w5yy88
title: Occurrence Download

description: A dataset containing 1966 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
}

 The dataset includes 1966 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002060-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.89brzf
title: Occurrence Download

description: A dataset containing 37201 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Northeast Area Monitoring and Assessment Program Near Shore Trawl Survey (NEAMAP)"
 ]
}

 The dataset includes 37201 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002062-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.