cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14440770
title: Leaching of Microplastics Enhanced Through Interspecific Soil Meso- and Macrofaunal Interactions

description: This dataset encompasses various parameters related to soil fauna survival, microplastic recovery, soil measurements, biweekly analyses of soil and leachate and earthworm identification.
description: The data is split into 5 parts:

Part 1 – Soil fauna survival: The dataset contains 10 survival classifications of the soil organisms added to each soil column. The data is stored in file ESR10_31.csv while meta data can be found in ESR10_31.pdf.

Part 2 – Microplastic recovery from soil columns: The dataset contains 2 parameters on polyethylene microplastics extracted from the final soil columns; where they were extracted and how many were extracted. The data is stored in file ESR10_32.csv while meta data can be found in ESR10_32.pdf.

Part 3 – Soil Measurements: The dataset contains 8 soil parameters of the entire soil column at the start and end of the experimental period. The data is stored in file ESR10_33.csv while meta data can be found in ESR10_33.pdf.

Part 4 – Biweekly soil column, leachate and lab analyses: The dataset contains 16 parameters of the soil, leachate and laboratory measured every 2 weeks over the entire 18-week incubation period. The data is stored in file ESR10_34.csv while meta data can be found in ESR10_34.pdf.

Part 5 – Earthworm Identification: The dataset contains 6 parameters of the earthworms taxonomic classification and numbers at different life stages. The data is stored in file ESR10_35.csv while meta data can be found in ESR10_35.pdf.
DOI: 10.5281/zenodo.14440771
title: Leaching of Microplastics Enhanced Through Interspecific Soil Meso- and Macrofaunal Interactions

description: This dataset encompasses various parameters related to soil fauna survival, microplastic recovery, soil measurements, biweekly analyses of soil and leachate and earthworm identification.
description: The data is split into 5 parts:

Part 1 – Soil fauna survival: The dataset contains 10 survival classifications of the soil organisms added to each soil column. The data is stored in file ESR10_31.csv while meta data can be found in ESR10_31.pdf.

Part 2 – Microplastic recovery from soil columns: The dataset contains 2 parameters on polyethylene microplastics extracted from the final soil columns; where they were extracted and how many were extracted. The data is stored in file ESR10_32.csv while meta data can be found in ESR10_32.pdf.

Part 3 – Soil Measurements: The dataset contains 8 soil parameters of the entire soil column at the start and end of the experimental period. The data is stored in file ESR10_33.csv while meta data can be found in ESR10_33.pdf.

Part 4 – Biweekly soil column, leachate and lab analyses: The dataset contains 16 parameters of the soil, leachate and laboratory measured every 2 weeks over the entire 18-week incubation period. The data is stored in file ESR10_34.csv while meta data can be found in ESR10_34.pdf.

Part 5 – Earthworm Identification: The dataset contains 6 parameters of the earthworms taxonomic classification and numbers at different life stages. The data is stored in file ESR10_35.csv while meta data can be found in ESR10_35.pdf.
DOI: 10.15468/dl.h377yr
title: Occurrence Download

description: A dataset containing 123 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Monarda citriodora Cerv. ex Lagasca"
 ]
}

 The dataset includes 123 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044187-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14337919
title: Interactions of MPs on soil meso- and macro-fauna

description: This dataset includes information on reproduction and mortality of soil organisms, bacterial abundance at various taxonomic levels, earthworm biomass changes, soil physiochemistry, and infrared absorbance readings of pristine and UV-aged polyethylene microplastics.
description: The data is split into 9 parts:

Part 1 – Reproduction and mortality: Count of adults and juveniles to determine mortality and reproduction. (e.g. the data set contains 15 properties of entire soil profiles determined at 606 locations). The data is stored in file ESR10_11.csv while meta data can be found in ESR10_11.pdf

Part 2 – Phylum ASV abundance: Dataset contains 55 bacterial phyla with Amplicon Sequence Variants (ASV) count in each sample to represent the abundance of each bacterial phylum present among the intestines of the exposed earthworms. Give brief information. The data is stored in file ESR10_12.csv while meta data can be found in ESR10_12.pdf

Part 3 – Family ASV abundance: Dataset contains 577 bacterial families with Amplicon Sequence Variants (ASV) count in each sample to represent the abundance of each bacterial family present among the intestines of the exposed earthworms. The data is stored in file ESR10_13.csv while meta data can be found in ESR10_13.pdf

Part 4 – Genus ASV abundance: Dataset contains 1347 bacterial genera with Amplicon Sequence Variants (ASV) count in each sample to represent the abundance of each bacterial genus present among the intestines of the exposed earthworms. The data is stored in file ESR10_14.csv while meta data can be found in ESR10_14.pdf

Part 5 – PCoA weighted UniFrac distances: Dataset contains 3 vertices for each sample to describe a coordinate used for comparing biological communities of bacteria from the gut of the earthworms. Weighted UniFrac accounts for abundance of observed earthworm gut bacterial. The data is stored in file ESR10_15.csv while meta data can be found in ESR10_15.pdf

 

Part 6 – PCoA unweighted UniFrac distances: Dataset contains 3 vertices for each sample to describe a coordinate used for comparing biological communities of bacteria from the gut of the earthworms. Unweighted UniFrac considers observed earthworm gut bacteria presence or absence. The data is stored in file ESR10_16.csv while meta data can be found in ESR10_16.pdf

 

Part 7 – Earthworm biomass change: Dataset consists of earthworm mass measured before and after experiment. The data is stored in file ESR10_17.csv while meta data can be found in ESR10_17.pdf

Part 8 – Soil physiochemistry: Dataset consists of soil pH and water content measured before and after experiment. The data is stored in file ESR10_18.csv while meta data can be found in ESR10_18.pdf

Part 9 – ATR table: Give brief information. Dataset consists of 3 replicates from each pristine and UV-aged PE-MP and their absorbance reading along the infrared spectrum. The data is stored in file ESR10_19.csv while meta data can be found in ESR10_19.pdf
DOI: 10.5281/zenodo.14337920
title: Interactions of MPs on soil meso- and macro-fauna

description: This dataset includes information on reproduction and mortality of soil organisms, bacterial abundance at various taxonomic levels, earthworm biomass changes, soil physiochemistry, and infrared absorbance readings of pristine and UV-aged polyethylene microplastics.
description: The data is split into 9 parts:

Part 1 – Reproduction and mortality: Count of adults and juveniles to determine mortality and reproduction. (e.g. the data set contains 15 properties of entire soil profiles determined at 606 locations). The data is stored in file ESR10_11.csv while meta data can be found in ESR10_11.pdf

Part 2 – Phylum ASV abundance: Dataset contains 55 bacterial phyla with Amplicon Sequence Variants (ASV) count in each sample to represent the abundance of each bacterial phylum present among the intestines of the exposed earthworms. Give brief information. The data is stored in file ESR10_12.csv while meta data can be found in ESR10_12.pdf

Part 3 – Family ASV abundance: Dataset contains 577 bacterial families with Amplicon Sequence Variants (ASV) count in each sample to represent the abundance of each bacterial family present among the intestines of the exposed earthworms. The data is stored in file ESR10_13.csv while meta data can be found in ESR10_13.pdf

Part 4 – Genus ASV abundance: Dataset contains 1347 bacterial genera with Amplicon Sequence Variants (ASV) count in each sample to represent the abundance of each bacterial genus present among the intestines of the exposed earthworms. The data is stored in file ESR10_14.csv while meta data can be found in ESR10_14.pdf

Part 5 – PCoA weighted UniFrac distances: Dataset contains 3 vertices for each sample to describe a coordinate used for comparing biological communities of bacteria from the gut of the earthworms. Weighted UniFrac accounts for abundance of observed earthworm gut bacterial. The data is stored in file ESR10_15.csv while meta data can be found in ESR10_15.pdf

 

Part 6 – PCoA unweighted UniFrac distances: Dataset contains 3 vertices for each sample to describe a coordinate used for comparing biological communities of bacteria from the gut of the earthworms. Unweighted UniFrac considers observed earthworm gut bacteria presence or absence. The data is stored in file ESR10_16.csv while meta data can be found in ESR10_16.pdf

 

Part 7 – Earthworm biomass change: Dataset consists of earthworm mass measured before and after experiment. The data is stored in file ESR10_17.csv while meta data can be found in ESR10_17.pdf

Part 8 – Soil physiochemistry: Dataset consists of soil pH and water content measured before and after experiment. The data is stored in file ESR10_18.csv while meta data can be found in ESR10_18.pdf

Part 9 – ATR table: Give brief information. Dataset consists of 3 replicates from each pristine and UV-aged PE-MP and their absorbance reading along the infrared spectrum. The data is stored in file ESR10_19.csv while meta data can be found in ESR10_19.pdf
DOI: 10.15468/dl.stthyd
title: Occurrence Download

description: A dataset containing 1004 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scorpaena maderensis Valenciennes, 1833",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 1004 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044188-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tcqgwu
title: Occurrence Download

description: A dataset containing 78209 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rosa multiflora Thunb."
 ]
}

 The dataset includes 78209 records from 520 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044185-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57967/hf/3847
title: finemath
DOI: 10.15468/dl.qraerg
title: Occurrence Download

description: A dataset containing 17119 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Amaranthus viridis L."
 ]
}

 The dataset includes 17119 records from 663 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044190-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9zcryk
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cucullia santonici",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "HasCoordinate is true"
 ]
}

 The dataset includes 120 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005061-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13534693
title: BOS Kemdikbud
DOI: 10.57745/j9jy5g
title: batiments__29.prj
DOI: 10.57745/gofgcw
title: batiments__29.dbf
DOI: 10.57745/nqcsrj
title: infos__29.txt
DOI: 10.57745/x0v6cy
title: batiments__48.cpg
DOI: 10.57745/vbhy1w
title: batiments__48.shp
DOI: 10.57745/ylp24v
title: batiments__48.shx
DOI: 10.5281/zenodo.17314673
title: Data Set Related to Manuscript "Structure of South Peruvian Upper Crust Revealed by Magnetotellurics and Shallow Seismicity" submitted to Geochemistry, Geophysics, Geosystems

description: This project was developed within the framework of the agreement between the Geophysical Institute of Peru (https://www.gob.pe/igp) and the Institute for Development Research (https://ird.fr/peru).

DataBroadband MT data are recorded in April 2023 using Metronix instruments (see main text).Edi files are produced with ProcMT and FFMT software as explained in the main text. Meta data are in edi-files.

Acknowledgments.

The project was developed within the framework of the agreement between the Geophysical Insti-tute of Peru (https://www.gob.pe/igp) and the Institute for Development Research (https://ird.fr/peru). The magnetotelluric data acquisition conducted in April 2023 was funded by IRD, IGP, ISTerre, and the "Tellus Program of CNRS-INSU." The calculations presented in this paper were performed using the GRICAD infrastructure (https://gricad.univ-grenoble-alpes.fr), with the support of the Grenoble and Chambéry research communities. José Luis Torres is funded by the French-Peruvian doctoral school in Engineering Sciences and Geosciences (EDF-PCIG, Rectoral Resolutions No. 504/2024), by the CONCYTEC-PROCIENCIA under the framework of the contest "Undergraduate and Postgraduate Thesis in Science, Technology, and Technological Innovation - Contest E073-2024-01" (contract number PE501091976-2024).  Finally, we thank Ana Kelbert, Gary Egbert, and particularly Naser Meqbel for making ModEM and 3D-Grid available to us, and for their continuous support.
DOI: 10.5281/zenodo.17314674
title: Data Set Related to Manuscript "Structure of South Peruvian Upper Crust Revealed by Magnetotellurics and Shallow Seismicity" submitted to Geochemistry, Geophysics, Geosystems

description: This project was developed within the framework of the agreement between the Geophysical Institute of Peru (https://www.gob.pe/igp) and the Institute for Development Research (https://ird.fr/peru).

DataBroadband MT data are recorded in April 2023 using Metronix instruments (see main text).Edi files are produced with ProcMT and FFMT software as explained in the main text. Meta data are in edi-files.

Acknowledgments.

The project was developed within the framework of the agreement between the Geophysical Insti-tute of Peru (https://www.gob.pe/igp) and the Institute for Development Research (https://ird.fr/peru). The magnetotelluric data acquisition conducted in April 2023 was funded by IRD, IGP, ISTerre, and the "Tellus Program of CNRS-INSU." The calculations presented in this paper were performed using the GRICAD infrastructure (https://gricad.univ-grenoble-alpes.fr), with the support of the Grenoble and Chambéry research communities. José Luis Torres is funded by the French-Peruvian doctoral school in Engineering Sciences and Geosciences (EDF-PCIG, Rectoral Resolutions No. 504/2024), by the CONCYTEC-PROCIENCIA under the framework of the contest "Undergraduate and Postgraduate Thesis in Science, Technology, and Technological Innovation - Contest E073-2024-01" (contract number PE501091976-2024).  Finally, we thank Ana Kelbert, Gary Egbert, and particularly Naser Meqbel for making ModEM and 3D-Grid available to us, and for their continuous support.
DOI: 10.57745/cm43km
title: batiments__48.dbf
DOI: 10.57745/jotynv
title: batiments__48.prj
DOI: 10.57745/wqadkt
title: images_06__48.tar.gz
DOI: 10.57745/jytfda
title: images_11__48.tar.gz
DOI: 10.57745/n60nrp
title: images_00__48.tar.gz
DOI: 10.57745/p5sclv
title: images_03__48.tar.gz
DOI: 10.57745/gcxugr
title: images_07__48.tar.gz
DOI: 10.57745/z9gogv
title: images_01__48.tar.gz
DOI: 10.57745/iffyjf
title: images_09__48.tar.gz
DOI: 10.57745/hzgvbt
title: images_05__48.tar.gz
DOI: 10.57745/tzmdxo
title: images_08__48.tar.gz
DOI: 10.57745/amq4hw
title: images_02__48.tar.gz
DOI: 10.57745/fllwmp
title: images_10__48.tar.gz
DOI: 10.57745/hpr0v9
title: infos__48.txt
DOI: 10.57745/uzd7vx
title: images_04__48.tar.gz
DOI: 10.57745/f8h9ez
title: batiments__59.prj
DOI: 10.57745/wmoppv
title: batiments__59.shx
DOI: 10.57745/ejvwpm
title: batiments__59.dbf
DOI: 10.57745/a7waps
title: batiments__59.shp
DOI: 10.57745/bxoipi
title: batiments__59.cpg
DOI: 10.57745/ob9eep
title: infos__59.txt
DOI: 10.15468/dl.gqwapp
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Opsaridium maculicauda"
 ]
}

 The dataset includes 4 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005744-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1164188.10fu
title: SH1164188.10FU

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/sh1164189.10fu
title: SH1164189.10FU

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/sh1164191.10fu
title: SH1164191.10FU

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/sh1164194.10fu
title: SH1164194.10FU

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/sh1164195.10fu
title: SH1164195.10FU

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/sh1164196.10fu
title: SH1164196.10FU

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.