cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26186/150687
title: SSCN-SEGMENT-2-C Apollo Marine Park - Shallow Waters Bathymetry 2024 (20240001S)

description: This dataset is part of a broader survey carried out by EGS Survey Pty Ltd onboard the survey vessel RV Bold Explorer (RV BE) during the SUBCO Subsea Cable Network (SSCN) cable route survey.
The area is confined to the data within the Apollo Marine Park and was acquired between 24th Februarfy 2024 and the 5th March 2024.
The SUBCO Subsea Cable Network (SSCN) comprises a trunk route between Perth (Western Australia) and Sydney (New South Wales) with branches to Garden Island (Western Australia), Adelaide (South Australia), and Torquay (Victoria).
EGS Australia was contracted by OMS to supply hydrographic, geophysical, and geotechnical survey services, to provide data for engineering, construction, and subsequent maintenance of the SSCN Segment 2-C (BU TQW up to 206.3m WD). The primary purpose of the survey is to determine a viable and secure route for the cable system that is clear of excessive slopes (&gt;6°), sea floor conditions that will adversely affect ploughing and burial of the cable, and obstacles such as rock outcrops, cable spans, existing cables, pipelines, shipwrecks etc.
The SSCN Segment 2-C (BU TQW up to 206.3m WD) survey comprised an investigation of bathymetry, seabed features and shallow geology along the proposed route.
This dataset is not to be used for navigational purposes.

Not to be used for navigational purposes
DOI: 10.25919/845m-8v38
title: NBDL-HK3SXDVKJ2NAZW
DOI: 10.26186/150712
title: FK150301 Henderson Perth Canyon to Henderson Bathymetry 2015 (4441/20150012S)

description: The FK150301 bathymetry Survey/Acquisition was acquired by University of Western Australia onboard the Research Vessel Falkor during the period 1st of March 2015 to 12th March 2015 using the Sensor/Instrument Kongsberg EM302 (30 kHz), EM710 (30 kHz) 
 
A primary goal for the mission was to run ROV (Remotely Operated Vehicle) surveys at various depths to assess what animals might be found, their abundance, and the best sites for more focused research. The researchers expected to find a range of species including corals, sponges, sea fans, sea pens, urchins, sea stars, and large fish including sharks. While researchers had ideas of what they would see, having never actually explored the canyon there was no telling what they might find. Species new to science are always a possibility, especially during deeper dives. 
 
Appropriate acknowledgment must be given to both the original scientists (Professor Malcolm McCulloch)(https://www.marine-geo.org/tools/search/DataSets.php?data_set_uids=22296,22297) and to the Marine Geoscience Data System (www.marine-geo.org).

This dataset is published with the permission of the CEO, Geoscience Australia.

Not to be used for navigational purposes
DOI: 10.25919/kxkc-km89
title: NBDL-HK3SZKTYHDV25Q
DOI: 10.25919/44we-x681
title: NBDL-HK3SXDXJK32GHZ
DOI: 10.26186/150693
title: SI 1037 Dampier Marine Park (South) (HIPP SI 1037) Bathymetry 2024 (20240003S)

description: The Dampier Marine Park (South) bathymetry survey was acquired for the Australian Hydrographic Office (AHO) during the period 15 Jul 2024 – 31 Jan 2025. This is a contracted survey conducted for the Australian Hydrographic Office by DMAL as part of the Hydroscheme Industry Partnership Program. The survey area is Dampier Marine Park, WA.

This dataset is not to be used for navigational purposes.

Not to be used for navigational purposes
DOI: 10.25919/ch0s-cc58
title: NBDL-HK3SZKVKQDSGGK
DOI: 10.25919/0pg5-1b15
title: NBDL-HK3SZKW8PD93MG
DOI: 10.26186/150706
title: Port Phillip Bay TieLines (Sandringham-St Leonards) Bathymetry 2021 (4894/20210010S)

description: The Port Phillip Bay bathymetry tielines survey was acquired by Deakin University Marine Mapping lab onboard the Motor Vessel Yolla over one day in 2021 (13/12) using a Kongsberg EM2040c. These data were collected to assess the movement of sediment through time.

Not to be used for navigational purposes
DOI: 10.25919/97ps-9r11
title: NBDL-HK3SZKV7QDS3Q3
DOI: 10.25919/1ap5-dg73
title: NBDL-HK3T5NRCJR63KE
DOI: 10.26186/150709
title: BMRG06MV Fremantle Southeast Indian Ridge to Port Hedland Bathymetry 1996 (1154/19960003S)

description: The BMRG06MV bathymetry survey was acquired by Bishop Museum, Hawaii and the University of California San Diego onboard the Scripps Institution of Oceanography (UCSD/SIO) Research Vessel Melville from the 22 February to 13 April 1996 using the Seabeam 2000 sonar system.
 
The bathymetry dataset was acquired while the Research Vessel Melville was transiting from Fremantle to Port Headland.
 
This dataset contains the 128m-210m resolution, 32-bit geotiffs of the BMR06MV survey produced from the processed SeaBeam system using the CARIS HIPS and SIPS software. 

Appropriate acknowledgment must be given to both the original scientists (Orcutt, John) (http://www.marine-geo.org/tools/search/entry.php?id=BMR06MV#datasets) and to the Marine Geoscience Data System (www.marine-geo.org).

Not to be used for navigational purposes
DOI: 10.25919/9q0x-m298
title: NBDL-HK3SZKXKGD8V34
DOI: 10.25919/ykdj-wq09
title: NBDL-HK3SZKX8PD8G0G
DOI: 10.26186/150679
title: SSCN-SEGMENT-2-E Beagle Marine Park - Shallow Waters Bathymetry 2024 (20240002S)

description: This dataset is part of a broader survey carried out by EGS Survey Pty Ltd onboard the survey vessel RV Bold Explorer (RV BE) during the SUBCO Subsea Cable Network (SSCN) cable route survey.
The area is confined to the data within the Beagle Marine Park and was acquired between 7th March 2024 and the 4th April 2024.

The SSCN comprises a trunk route between Perth (Western Australia) and Sydney (New South Wales) with branches to Garden Island (Western Australia), Adelaide (South Australia), and Torquay (Victoria).
EGS Australia was contracted by OMS to supply hydrographic, geophysical, and geotechnical survey services, to provide data for engineering, construction, and subsequent maintenance of the SSCN Segment 2-E. The primary purpose of the survey is to determine a viable and secure route for the cable system that is clear of excessive slopes (&gt;6°), sea floor conditions that will adversely affect ploughing and burial of the cable, and obstacles such as rock outcrops, cable spans, existing cables, pipelines, shipwrecks, etc. This enables exact cable lengths, cable design and installation parameters to be defined to minimise problems over the designated life of the system.
This dataset is not to be used for navigational purposes.

Not to be used for navigational purposes
DOI: 10.25919/sfte-8w08
title: NBDL-HK3T892NPMBCBE
DOI: 10.25919/05yj-tg48
title: NBDL-HK48NMFTJQ0X7N
DOI: 10.26186/150623
title: Helens Rock Bathymetry 2013 (4888/20130019S)

description: The Helen's Rocky bathymetry survey was acquired by Deakin University Marine Mapping lab onboard the Motor Vessel Yolla over one day in 2013 (27/11) using a Kongsberg EM2040c.

Not to be used for navigational purposes
DOI: 10.25919/9fqj-4734
title: NBDL-HK3SXDXGQ32KC7
DOI: 10.26186/150694
title: Popes Eye Bathymetry 2018 (4893/20180002S)

description: The Popes Eye bathymetry survey was acquired by Deakin University Marine Mapping lab onboard the Motor Vessel Yolla over two days in 2018 (20/01/2018-21/01/2018) using a Kongsberg EM2040c. This survey was collected as part of Parks Victoria project to map all the marine parks within Victorian state waters.

Not to be used for navigational purposes
DOI: 10.25919/ghr9-j811
title: NBDL-HK3SXDXSN321BK
DOI: 10.25919/efxw-0p77
title: NBDL-HK3SZKTZQDV4P3
DOI: 10.26186/150705
title: Port Fairy Wave Energy Site Bathymetry 2021 (4892/20210005S)

description: The Port Fairy Wave Energy Site bathymetry survey was acquired by Deakin University Marine Mapping lab onboard the Motor Vessel Yolla over one day in 2021 (30/03) using a Kongsberg EM2040c. These data were collected to assess the impact of a wave energy structure placed on the seafloor.

Not to be used for navigational purposes
DOI: 10.15468/dl.4fmctn
title: Occurrence Download

description: A dataset containing 372 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sceloporus carinatus"
 ]
}

 The dataset includes 372 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013251-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17383313
title: Subduction Legacy and Its Control on the Spatial Heterogeneity of the Emeishan Large Igneous Province
DOI: 10.5281/zenodo.17745112
title: Subduction Legacy and Its Control on the Spatial Heterogeneity of the Emeishan Large Igneous Province
DOI: 10.15468/dl.mgastt
title: Occurrence Download

description: A dataset containing 131 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Itzaea sericea"
 ]
}

 The dataset includes 131 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013253-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q4wc5s
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sceloporus cryptus"
 ]
}

 The dataset includes 120 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013252-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ythek
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Polystichum otophorum"
 ]
}

 The dataset includes 56 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013254-251120083545085/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/13903439
title: Layline Shareholder activism dataset
DOI: 10.15468/dl.5qruj5
title: Occurrence Download

description: A dataset containing 116 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ixora coccinea"
 ]
}

 The dataset includes 116 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013255-251120083545085/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.30736643
title: Additional file 1 of Integrative multi-omics and single-cell transcriptomics reveal ARHGEF12 driving chemoresistance in bladder cancer

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.30736643.v1
title: Additional file 1 of Integrative multi-omics and single-cell transcriptomics reveal ARHGEF12 driving chemoresistance in bladder cancer

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.30736667
title: Additional file 1 of Cold adaptation and horizontal gene transfer shape Antarctic sponge microbiomes

description: Additional file 1: Supplementary Figure S1. Supplementary Figure S1. Exclusive and shared genes annotated between Antarctic, tropical, and temperate sponge microbiomes. Supplementary Figure S2. Presence/absence of genes encoding functions for cold adaptation in the microbiomes of Antarctic, tropical, and temperate sponges and Antarctic seawater. The metagenome sizes of all samples were normalized to the sample with the smallest size. The Ward method was used to perform clustering. Supplementary Figure S3. Percentage of genes encoding functions related to cold adaptation and metabolism non-significantly higher in Antarctic sponge microbiomes compared to their surrounding seawater and temperate and tropical sponge microbiomes. ****: p &lt; 0.0001, ***: p &lt; 0.001, **: p &lt; 0.01,*: p &lt; 0.05. ATM: Amino acid transport and metabolism, CTM: Carbohydrate transport and metabolism, EPC: Energy production and conversion, LTM: Lipid transport and metabolism, MAR: Metal and antibiotic resistance and metabolism. Supplementary Figure S4. Exclusive and shared csp genes between Antarctic, tropical, and temperate sponge microbiomes. Supplementary Figure S5. Association between the number of genes annotated and the number of horizontally transferred (HT) genes in each functional group based on different calculations: (A) The number of HT genes within each functional group, relative to the total number of HT genes. (B) The number of HT genes per total gene content within each functional group. Pearson was used to test correlations between the variables. ATM: Amino acid transport and metabolism, CTM: Carbohydrate transport and metabolism, EPC: Energy production and conversion, LTM: Lipid transport and metabolism, MAR: Metal and antibiotic resistance and metabolism, ICE: Machinery of Integrative and conjugative elements. Supplementary Figure S6. Putative genes horizontally acquired in MAGs of Antarctic sponge symbionts from MAGs of free-living bacteria in the surrounding seawater. The X-axis displays the sponge species (above) and the taxonomy of the recipient MAGs (below).
DOI: 10.6084/m9.figshare.30736667.v1
title: Additional file 1 of Cold adaptation and horizontal gene transfer shape Antarctic sponge microbiomes

description: Additional file 1: Supplementary Figure S1. Supplementary Figure S1. Exclusive and shared genes annotated between Antarctic, tropical, and temperate sponge microbiomes. Supplementary Figure S2. Presence/absence of genes encoding functions for cold adaptation in the microbiomes of Antarctic, tropical, and temperate sponges and Antarctic seawater. The metagenome sizes of all samples were normalized to the sample with the smallest size. The Ward method was used to perform clustering. Supplementary Figure S3. Percentage of genes encoding functions related to cold adaptation and metabolism non-significantly higher in Antarctic sponge microbiomes compared to their surrounding seawater and temperate and tropical sponge microbiomes. ****: p &lt; 0.0001, ***: p &lt; 0.001, **: p &lt; 0.01,*: p &lt; 0.05. ATM: Amino acid transport and metabolism, CTM: Carbohydrate transport and metabolism, EPC: Energy production and conversion, LTM: Lipid transport and metabolism, MAR: Metal and antibiotic resistance and metabolism. Supplementary Figure S4. Exclusive and shared csp genes between Antarctic, tropical, and temperate sponge microbiomes. Supplementary Figure S5. Association between the number of genes annotated and the number of horizontally transferred (HT) genes in each functional group based on different calculations: (A) The number of HT genes within each functional group, relative to the total number of HT genes. (B) The number of HT genes per total gene content within each functional group. Pearson was used to test correlations between the variables. ATM: Amino acid transport and metabolism, CTM: Carbohydrate transport and metabolism, EPC: Energy production and conversion, LTM: Lipid transport and metabolism, MAR: Metal and antibiotic resistance and metabolism, ICE: Machinery of Integrative and conjugative elements. Supplementary Figure S6. Putative genes horizontally acquired in MAGs of Antarctic sponge symbionts from MAGs of free-living bacteria in the surrounding seawater. The X-axis displays the sponge species (above) and the taxonomy of the recipient MAGs (below).
DOI: 10.6084/m9.figshare.30736670
title: Additional file 2 of Cold adaptation and horizontal gene transfer shape Antarctic sponge microbiomes

description: Additional file 2: Supplementary Table S1. Supplementary Table S1. Metadata associated with the Antarctic, tropical, and temperate sponge microbiomes and Antarctic seawater microbiomes used in this study. Asterisks in "Sponge_status" indicate apparent classification of LMA sponges based on alpha diversity and phylum composition. Supplementary Table S2. Quantity and quality parameters of metagenomes (contigs, genes, annotations). Supplementary Table S3. List and counts of non-redundant genes classified into cold adaptation functions across all analyzed metagenomes. Supplementary Table S4. List and counts of non-redundant genes classified into the analyzed metabolic, resistance, and conjugative functions across all analyzed metagenomes. Supplementary Table S5. Pairwise PERMANOVA comparisons for the effect of the environment on the gene composition of microbiomes based on Bray–Curtis dissimilarities. Significance: "." indicates p &lt; 0.05, "*" indicates p &lt; 0.01, "**" indicates p ≤ 0.001. Supplementary Table S6. Gene proportions (%), abundance (RPKG), and diversity (Shannon index) of the functional groups analyzed in this study. The functional groups comprise cold adaptation, amino acid transport and metabolism (ATM), carbohydrate transport and metabolism (CTM), energy production and conversion (EPC), lipid transport and metabolism (LTM), metal and antibiotic resistance and metabolism (MAR), and machinery of integrative and conjugative elements (ICE). Supplementary Table S7. Taxonomy-assignment and quantity and quality parameters of MAGs (contigs, genes, annotations). Supplementary Table S8. Donor and recipient taxa of horizontally transferred functions for cold adaptation and the type of HGT event.
DOI: 10.6084/m9.figshare.30736670.v1
title: Additional file 2 of Cold adaptation and horizontal gene transfer shape Antarctic sponge microbiomes

description: Additional file 2: Supplementary Table S1. Supplementary Table S1. Metadata associated with the Antarctic, tropical, and temperate sponge microbiomes and Antarctic seawater microbiomes used in this study. Asterisks in "Sponge_status" indicate apparent classification of LMA sponges based on alpha diversity and phylum composition. Supplementary Table S2. Quantity and quality parameters of metagenomes (contigs, genes, annotations). Supplementary Table S3. List and counts of non-redundant genes classified into cold adaptation functions across all analyzed metagenomes. Supplementary Table S4. List and counts of non-redundant genes classified into the analyzed metabolic, resistance, and conjugative functions across all analyzed metagenomes. Supplementary Table S5. Pairwise PERMANOVA comparisons for the effect of the environment on the gene composition of microbiomes based on Bray–Curtis dissimilarities. Significance: "." indicates p &lt; 0.05, "*" indicates p &lt; 0.01, "**" indicates p ≤ 0.001. Supplementary Table S6. Gene proportions (%), abundance (RPKG), and diversity (Shannon index) of the functional groups analyzed in this study. The functional groups comprise cold adaptation, amino acid transport and metabolism (ATM), carbohydrate transport and metabolism (CTM), energy production and conversion (EPC), lipid transport and metabolism (LTM), metal and antibiotic resistance and metabolism (MAR), and machinery of integrative and conjugative elements (ICE). Supplementary Table S7. Taxonomy-assignment and quantity and quality parameters of MAGs (contigs, genes, annotations). Supplementary Table S8. Donor and recipient taxa of horizontally transferred functions for cold adaptation and the type of HGT event.
DOI: 10.6084/m9.figshare.30736656
title: Additional file 7 of Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation

description: Supplementary Material 7. Supplementary Table 1. EC content in reconstructed metagenome assembled genomes annotated with KEGG and MetaCyc (related to Supplementary Figure 2).
DOI: 10.6084/m9.figshare.30736656.v1
title: Additional file 7 of Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation

description: Supplementary Material 7. Supplementary Table 1. EC content in reconstructed metagenome assembled genomes annotated with KEGG and MetaCyc (related to Supplementary Figure 2).
DOI: 10.6084/m9.figshare.30736659
title: Additional file 8 of Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation

description: Supplementary Material 8. Supplementary Table 2. Normalized cross-feeding interactions between top cross-feeding taxa in HB and NB communities (related to Figure 4 A).
DOI: 10.6084/m9.figshare.30736659.v1
title: Additional file 8 of Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation

description: Supplementary Material 8. Supplementary Table 2. Normalized cross-feeding interactions between top cross-feeding taxa in HB and NB communities (related to Figure 4 A).
DOI: 10.6084/m9.figshare.30736662
title: Additional file 9 of Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation

description: Supplementary Material 9. Supplementary Table 3. Linear model summary: impact of key metabolic hubs presence on cross-feeding activity. The response variable is the cross-feeding coefficient, which quantifies the degree of metabolic interactions within the community. Predictor variables included categorical levels of E. coli abundance (Ecoli_category:"NoEcoli","LowEcoli” (&lt;5% relative abundance),"HighEcoli (&gt;5% relative abundance)"), Bacteroides presence or absence that defines the community category (Bacteroides:"NB"or"HB"), the presence of key taxa such as Anaerostipes butyraticus (Abutyraticus_presence) and Lactobacillus crispatus (Lcrispatus_presence), and community size (comm_size).
DOI: 10.6084/m9.figshare.30736662.v1
title: Additional file 9 of Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation

description: Supplementary Material 9. Supplementary Table 3. Linear model summary: impact of key metabolic hubs presence on cross-feeding activity. The response variable is the cross-feeding coefficient, which quantifies the degree of metabolic interactions within the community. Predictor variables included categorical levels of E. coli abundance (Ecoli_category:"NoEcoli","LowEcoli” (&lt;5% relative abundance),"HighEcoli (&gt;5% relative abundance)"), Bacteroides presence or absence that defines the community category (Bacteroides:"NB"or"HB"), the presence of key taxa such as Anaerostipes butyraticus (Abutyraticus_presence) and Lactobacillus crispatus (Lcrispatus_presence), and community size (comm_size).
DOI: 10.6084/m9.figshare.30736665
title: Additional file 10 of Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation

description: Supplementary Material 10. Supplementary Table 4. Non-dietary metabolite exchanges between taxa across HB and NB communities (related to Supplementary Figure 6).
DOI: 10.6084/m9.figshare.30736665.v1
title: Additional file 10 of Metabolic modeling of microbial communities in the chicken ceca reveals a landscape of competition and co-operation

description: Supplementary Material 10. Supplementary Table 4. Non-dietary metabolite exchanges between taxa across HB and NB communities (related to Supplementary Figure 6).