dataesr/scientific-paragraphs-categorization huggingface dataset:
Demographic Inference The ABC software DILS (Demographic Inferences with Linked Selection by using ABC  [56] ) was used to determine which historical scenario of isolation versus gene flow might best explain the genetic structure observed today between the three Alviniconcha species in the Western Pacific ocean. In an approximate Bayesian computational framework, DILS compares summary statistics from simulated and observed datasets to identify plausible demographic scenarios and to jointly estimate population parameters such as effective population sizes, time of isolation, and past and contemporary gene flow between populations. It also takes into consideration changes in population size, local selective effects along the genome (variation in the effective size N e among loci), and semipermeable barriers to gene flow (variation in the effective migration rate me among loci).
Because DILS is designed to simulate divergence scenarios for a pair of populations, we reanalysed our RAD-seq dataset for the three pairs of species by running the Stacks population function using the common catalogue of loci described above, with r = 0. 8 and MAC = 4. Then, we only kept SNPs genotyped in at least 90% of the individuals. For the demographic inference, 5655 RAD loci and 265 individuals were used for the A. boucheti/A. strummeri pair, 8808 RAD loci and 495 individuals were used for the A. kojimai/A. boucheti pair, and 5775 RAD loci and 304 individuals were used for the A. kojimai/A. strummeri pair. Because DILS uses a random subsample of 1000 loci to estimate observed summary statistics, we ran 10 independent analyses for each pair of species, under the following main models: strict isolation (SI), ancient migration (AM), isolation with migration (IM), and secondary contact (SC).
During these runs, the method accounted for two events of instantaneous population size change (one when the ancestral population splits into two daughter populations and one at any later time). Finally, for each run, the program also tested whether N e and me are distributed heterogeneously along the genome (therefore accounting for the effect of linked selection and local barrier effects on gene flow along the genome). The goodness of fit of each run was estimated using the Euclidean distance between the observed and simulated summary statistics calculated with an accompanying Python script. Detailed parameter settings are provided in the Supplementary Materials (see example of detailed parameter settings section).
Following the Kraken filtering, around 5-10% of the initial reads of each individual were assigned to prokaryotes. The 90-95% remaining reads were then assembled in rnaSPAdes 3. 13. 1 using default parameters  [59]. The quality of the assembly was checked by looking at the remapping rate and by performing a Busco analysis. After sequence assembly, the resulting contigs were used in the Galaxy pipeline AdaptSearch (repository https://github. com/abims-sbr/adaptsearch accessed on 10 February 2022 ) to find orthologous sequences between species, estimate species divergence from the coding sequences, and find genes under positive selection. The first step of this pipeline is to filter transcripts to only keep one sequence per gene using both the length and the quality score of the transcripts and to perform an additional CAP3 assembly  [60].
Transcripts of the different species were then put together in orthogroups with Orthofinder  [61]. The sequences of orthogroups were aligned using BlastAlign  [62] , and the reading frame was identified from the species alignment with the in-house Python script CDSsearch (in the AdaptSearch suite) using Blastx against NCBI libraries. Finally, gene alignments were concatenated over the whole shared transcriptome and the alignment was used to reconstruct a phylogenetic tree with RAxML  [63]. This alignment of coding sequences was then used to estimate the standard diversity index (π) within species and the absolute divergence (d XY ) between species using DnaSP 6. 0  [41, 42]. The divergence accumulated at non-synonymous (d N ) and synonymous sites (d S ) along terminal branches, and their ratio was calculated with CodeML  [64].
Morphology We measured six shell traits from 700 Alviniconcha individuals. The distribution of the values of shell traits is shown in Supplementary Figure  S3. All measurements were significantly different between species (ANOVA, p < 0. 001), with A. boucheti having on average a larger shell (at all measured traits) than A. kojimai, and A. strummeri being the smallest species. Only a small fraction of the variance in shell traits seemed to be related to species identity (see PCA axis 2 in Figure  S5 ). This was due to the low power in discriminating species using solely shell dimensions measured (see LDA in Figure  S7 ). Since the reclassification of species using the whole dataset was correct for only 75% of the individuals (and below 2% for A. strummeri in particular), we did not further evaluate the capacity of the LDA using training and test subsets of the data.
ddRAD-seq Analysis along the Nuclear Genome The "raw" dataset (where an SNP is retained if genotyped in at least 80% of individuals within any species) contained 640,002 SNPs from 94,215 RAD loci. The distribution of these loci among species is shown in Figure  4. Almost 76% of the RAD loci sequenced in A. strummeri were also sequenced in at least one of the two other species, while this fraction was 57% in A. kojimai and 33% in A. boucheti. Further filtering on missing data of the 9365 loci in common across the three species led to a final dataset containing 60,084 biallelic SNPs on 4380 RAD loci genotyped in 498 individuals (triplicated removed). Among these SNPs, 80% were polymorphic within a  Further filtering on missing data of the 9365 loci in common across the three species led to a final dataset containing 60,084 biallelic SNPs on 4380 RAD loci genotyped in 498 individuals (triplicated removed).
Hydrothermal Vents in the Western Pacific Are Home to Three Sympatric Alviniconcha Species Hydrothermal vent gastropods of the genus Alviniconcha have been found in the Indian and Western Pacific oceans, where a total of six species have been described  [13, 14]. Although species were delineated using up to three mitochondrial and seven nuclear genes  [13, 14, 30] , the most discriminating genetic marker was the mitochondrial Cox1 gene  [13, 14]. Focusing on the three species A. boucheti, A. kojimai, and A. strummeri, which inhabit the Western Pacific, we found that the genetic divergence measured across the genome was consistent with the Cox1 mtDNA results used previously to delineate species. Reference transcriptome assemblies counting nearly 1. 2 million homologous sites across the three species and a RAD-seq dataset composed of over 4380 RAD loci sequenced in 36 to 250 individuals per species showed that the genetic divergence (measured as d XY ) was ca.
2% between A. kojimai and A. strummeri and ca. 3% between A. boucheti and the two other species (Table  2 ). These values are consistent with the levels of genetic divergence generally observed between reproductively isolated species  [27]. The SNP dataset (over 60,000 SNPs) derived from homologous RAD sequences also indicated that the genetic differentiation between species was strong (over 69% of the genetic variance explained by the first two principal components, Figure  6 , and pairwise F ST values between 0. 84 and 0. 92 from shared polymorphic loci, Table  2 , while F ST across basins within each species was between 0. 003 and 0. 02). Together with the mtDNA network and divergence estimates we obtained for the same set of individuals, all our results support the previous conclusions of  Johnson et al.
A Long History of Divergence in Allopatry All genomic datasets (mtDNA Cox1, transcriptomes, and nuclear RAD-seq) indicated that the divergence (measured either as d XY or d A , Table  2 ) between A. boucheti and the ancestor of the two other species was ca. 1. 4 to 1. 6 times greater than the divergence between A. kojimai and A. strummeri. This was further confirmed by the fixation rates of non-synonymous (d N ) and synonymous mutations (d S ) in the three pairs of species, both of which indicate that A. boucheti was ca. 1. 6 times more divergent than the two other species in the two coding compartments (mtDNA Cox1 and transcriptomes). The older separation of A. boucheti from the two other species is also supported by the fact that it differs from its two congenerics by a different shell columella shape and a distinct endosymbiosis with Campylobacteria  [14, 65, 72].
The almost equal and high divergence between A. boucheti and the two other species in all genomic compartments suggests that mutations were accumulated at the same rate between the two other species or that the demography of A. kojimai and A. strummeri was very similar. These results, therefore, suggest that the genetic divergence between species mostly reflects the time elapsed since speciation events. This finding is important because it is a critical assumption when using fossil-calibrated phylogenies for dating lineage splitting, as recently performed by Breusing et al. [14]. With mutations accumulating globally at a constant rate along lineages, ratios of divergence between species (e. g. , d A,sp1 /d A,sp2 ) appear relatively constant when measured from distinct genomic datasets, as explained above.
Conclusions This study showed the co-occurrence of three divergent Alviniconcha species (A. kojimai, A. boucheti, and A. strummeri) across the five back-arc Basins of the Western Pacific Ocean. The number of accumulated non-synonymous and synonymous substitutions between A. boucheti/A. kojimai and A. boucheti/A. strummeri was nearly identical on all genomic datasets, suggesting that divergence is proportional to the time since species separation. However, admixture analyses and demographic inferences clearly supported a scenario in which the three species evolved without gene flow for a long period of time (different geographic origins), followed by a relatively recent secondary contact with resumption of gene flow despite the strong accumulated divergence between species. These secondary contacts could coincide with the opening of the Lau Basin from 1.
Inter-specific genetic divergence and differentiation for the three genetic datasets: Cox1 mitochondrial gene (599 bp), ddRAD-seq SNPs(60,084 SNPs), and nuclear encoding RNAseq (1,186,131 bp). d A : net divergence; d XY : absolute divergence; F ST : genetic differentiation; d N : rate of non-synonymous substitutions; d S : rate of synonymous substitutions.
Acknowledgments: We are deeply grateful to the crew of the  RV L'Atalante , as well as the crew of the ROV 6000 Victor, during the ChuBacArc 2019 expedition, without whom nothing would have been possible. We also thank  John Parianos  and  Paul Lahari  of  Nautilus Minerals  for sharing information about their Solwara mining prospects in the Manus Basin, as well as  Valérie Cueff  for her help with the dissections on board the boat. We sincerely thank  Camille Roux  for his help with DILS analyses and the production of a new python script to produce quantitative estimates of goodness of fit. We also thank the core cluster of the  LBBE laboratory  ( UMR CNRS 5558 ) for running the demographic inference. This work benefited from access to the  Biogenouest Genomer platform at Station Biologique de Roscoff , and we are grateful to the  Roscoff Bioinformatics platform ABiMS  (http://abims.
Acknowledgements We dedicate this article to our late colleague  Sandrine Pagès-Camagna  who has initiated the work on these samples during her PhD thesis. The  Department of Egyptian Antiquities of the Louvre Museum  and especially the chief curator  Hélène Guichard  are warmly thanked for giving us access to the archaeological pigments. The authors thank  Serge Cohen  ( IPANEMA ) for the design of the sample holder,  Maëva L'Héronde  ( IPA-NEMA ) for processing the SEM data and  Quentin Jacquet  for renement. We thank SOLEIL for the provision of synchrotron radiation time and we would like to thank  Angélique Rouquié  for her assistance during synchrotron experiments. MG and LB acknowledge support from the  European Commission program IPERION CH  (Grant Agreement 654028). This work is carried out within the framework of the  Atoms for Heritage Collaborating Centre associating Université Paris-Saclay  and the  International Atomic Energy Agency (IAEA).
Materials and methods The onshore successions (Zalidou and Aït Hamouch) span the late Berriasian to early Hauterivian covering the entire Valanginian. The offshore DSDP Leg 50 Hole 416A spans the Valanginian stage  ( Čepek and Gartner, 1980). Samples for calcareous nannofossils, calcium carbonate content, and carbon-isotope analyses were collected from different lithologies (except sandstones). The sampling interval was on average 0. 3 m in Zalidou, 0. 5 m in Aït Hamouch, and 5 m in Hole 416A. Both macrofossils and nannofossil smear slides are curated at the Collections de Géologie de l'Observatoire des Sciences de l'Univers de Grenoble (OSUG), with an appropriate UJF-ID number. "OSUG-COL-LECTIONS" is a database of rocks, minerals, and fossils (https://web. collections. osug. fr, OSUG, UGA; doi:https://doi.
To consider the inherent counting uncertainty, binomial proportion confidence intervals for relative abundances were computed based on the 'exact' Clopper-Pearson method using the PAST software  (Hammer et al. , 2001; Suchéras-Marx et al. , 2019). Additionally, diversity indices were calculated. Nannoconus spp. were excluded from the calculation of sample diversity indices, absolute/relative abundances, and accumulation rates of other taxa because of their uncertain biological affinity  (Aubry et al. , 2005). The counting and the different calculation formulae are given in the Supplementary Table.
Acknowledgements This work benefited from financial support by the  Ministries  of foreign affairs from France and  Morocco  ( PHC  project n •  031/STU/13 ), the  French IRD, Campus France , and various grants from the  ISTerre laboratory (Grenoble) , the  Laboratoire de Géologie de Lyon , the  OSUG@2020 Labex , the  CNRS SYSTER program , and IODP France soutien post-cruise. Additional grants were provided by the  French government (bourse BGF) ,  the doctoral school TUE of the Grenoble-Alpes University , and by the  TRB team of ISTerre laboratory. We are grateful to the editor  Ric Jordan  and two anonymous reviewers for both corrections and comments which greatly improved the quality of an earlier version of the manuscript.
Acknowledgements. The research presented in this paper is funded by  BELSPO (Belgian Science Policy Office)  in the frame of the  STEREO III  programme -project  ECOPROPHET  ( SR/00/334 ), and co-funded by  EUMETSAT  ( LSA SAF program  for  CDOP-3 ) and the  Belspo/ESA   Prodex Program  ( PEA 4000110695 ). This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks:  AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, TCOS-Siberia , and  USCCC. The FLUXNET eddy covariance data processing and harmoniza-.
| DSDDP 5017-1-A Holocene chronology The 456-meter sedimentary core 5017-1-A was extracted from the deepest part of the lake at 300-m water column depth (~720 m below mean sea level) at 31°30′28. 98″N, 35°28′15. 60″E. The chronology of the investigated sediment sequence for Holocene sediments (Figure  2a ) is based on a linear interpolation of calibrated radiocarbon ages derived from terrestrial plant remains from site 5017-1  (Kitagawa et al. , 2017; Neugebauer et al. , 2014 ; Figure  2b ). The calibration was done using the IntCal13 calibration dataset  (Reimer et al. , 2013)  within the OxCal 4. 3 software.
0 ) vs. ( 34 S SO 4 -34 S SO 4 ,0 ) plot for a range of SO 4 2-sources (marine, lacustrine, groundwater and subsurface pore fluids), and Dead Sea gypsum deposits. Values for 34 S SO 4 ,0 and 18 O SO 4 ,0 are the lowest within the individual datasets unless stated otherwise. Datasets presented: shelf sediments from site PC-6 in the Mediterranean Sea (open triangles) with 34 S SO 4 ,0 = 20. 2‰ and 18 O SO 4 ,0 = 9. 4‰ (Rubin-Blum et al. , 2014); primary gypsum layers deposited in and around the Dead Sea dating back to the last glacial period (crosses) with estimated initial Lake Lisan SO 4 2-values of 34 S SO 4 ,0 = 10‰ and 18 O SO 4 ,0 = 10‰ (Torfstein & Turchyn, 2017); groundwater at Ein Gedi along the Dead Sea coast (black diamonds) with 34 S SO 4 ,0 = 15. 9‰ and 18 O SO 4 ,0 = 13. 7‰ (Avrahamov et al.
g. , OSL, AAR, cosmogenic nuclides). Previously, speleothems from the NCC have only been dated with the U-Th chronometer  17, 31  ; our new data significantly improve the existing speleothem chronology and extend it by ~70%. Improved knowledge of the antiquity of the Naracoorte Cave Complex. Although previously reported ages for the Naracoorte region remain inconclusive, palaeomagnetic data suggest that cave development may have begun in the Early Pleistocene. The existing speleothem chronology  17, 31, 32  has been of limited use in this context because the system is clearly beyond the reach of the U-Th chronometer. Among the new U-Pb ages from this study are speleothems that were growing in several caves as early as 1. 34 ± 0. 04 Ma (stalagmite ALEX-11), 1. 23 ± 0. 08 Ma (flowstone WB-6) and 1.
All samples were corrected with a Naracoorte-specific initial 230 Th/ 232 Th ratio of 0. 65 ± 0. 35 using stratigraphic constraint as described in Hellstrom  50. With the 234 U and 230 Th halflife values of Cheng et al. 30  and Monte-Carlo iterations to solve Eq. (1) in Hellstrom  50  , we calculated corrected ages and their 2se uncertainty for which the uncertainties of the measured activity ratios as well as the assumed initial 230 Th/ 232 Th are fully propagated (Supplementary Data 1 Table  1 ). Any ages that exceeded the infinite-age isochron or with an infinite upper bound uncertainty were selected for U-Pb dating (Supplementary Data 1 Table  2 ). For this, we used five or more aliquots per speleothem sample obtained using a hand-held dental drill. The U-Th and reconnaissance U-Pb analyses revealed that Naracoorte speleothems contain very low U concentrations (between 0.
Once dried, the U and Pb fractions were dissolved in nitric acid and separately measured on a Nu Instruments Plasma MC-ICPMS following Woodhead et al. 48. We corrected for instrumental mass bias effects using the sample's internal 238 U/ 235 U ratio (137. 88) for U and reference material NIST SRM 981 for Pb. Instrument data processing, including mass bias and drift corrections, was performed with an in-house importer within the Iolite environment  51, 52  , after which the results were blank-corrected and isotope-dilution calculations were performed. Where possible, isochrons were constructed using the robust statistical approach of Powell et al. 53  , implemented using the software of Pollard et al. 54. In cases where the "spine width" was found to exceed the upper 95% confidence limit (indicating that the dataset did not meet the assumptions of this approach), a Model 2 fit 55 was implemented instead.
Finally, samples were dehydrated in ethanol, and mounted in glycerol on glass slides. Pollen and charcoal were counted at ×320 and ×640 magnifications on a Zeiss Axiolab A1 compound microscope fitted with N-Achroplan objectives. Charcoal was defined as all angular, opaque objects >10 µm in diameter. Pollen percentage data will be presented in a subsequent publication. Potential biases. To avoid a sampling bias, we randomly collected speleothem rubble samples throughout the caves with respect to distance from the cave entrance. We did not record the spatial distribution of our samples: some rubble samples were in situ, evidenced by intact parts of stalagmites and stalactites on cave floors and roofs but many other samples were clearly transported small distances, most likely by the cave management when preparing for visitor paths in show caves.
More importantly, our conclusions are unaffected by whether the rubble samples are in situ or transported within a cave. The age difference between top and base of individual stalagmites is small on average (Supplementary Table  3 ), and so any "sample position bias" is unlikely to influence our results significantly over the timescale of the dataset. The aliquots targeted for charcoal and pollen analysis were mostly taken from the same section as the aliquot for U-Th dating, but not always. The pollen/ charcoal aliquots had to be an order of magnitude larger than the U-Th aliquots in order to extract a statistically significant amount of charcoal fragments and pollen. In this paper, the point is that there is a major increase in charcoal density after ca 250 ka. For that pattern to be an artefact of mismatches between sample U-Th age and the age of the sample's charcoal/pollen aliquot, the mismatch would need to be at least tens of kyr, probably more (rather than single-digit kyr differences, which are possible).
We top-bottom dated several stalagmites from a larger pool of NCC samples (not all included in this study) to understand the typical lifespan of a speleothem (Supplementary Table  3  and Supplementary Fig. 4 ). The results show that NCC stalagmites are relatively short-lived, i. e. , not longer than ~27 ka on average. Most charcoal/pollen aliquots were sampled within the age uncertainty of the U-Th aliquot, and, on the timescale of the entire dataset, any age discrepancy between U-Th and pollen/charcoal aliquots will not change the conclusions of this paper. We believe climate/ecosystem changes are not the primary cause of the changes in charcoal/pollen concentrations at NCC over the past ~1 Ma. This is because, first, if our pollen and charcoal concentration records were primarily responses to vegetation change, then the low pollen and charcoal concentrations in most samples prior to ca.
Acknowledgements We acknowledge that we worked on the lands of the First Nations Peoples who have been the Custodians for thousands of years and we acknowledge and pay our respects to their Elders past and present. We thank the  Naracoorte Caves management team  for providing access to the caves on the park as well as the owners of caves on private properties. We also thank our Naracoorte research partners  Terre à Terre Pty Ltd, Department of Environment and Water, Naracoorte Lucindale Council, Wrattonbully Wine Industries Association Inc, South Australian Museum , and  Defence Science and Technology Group. Thanks also to  Petra Bajo ,  John Engel ,  Serene Paul ,  Roland Maas  for laboratory and data processing assistance. R. W. thanks  Robyn Pickering  for her support. We thank  Patrick Moss ,  Sylvia Reichelmann  and one anonymous reviewer for their comments and suggestions.
Data availability The datasets generated during the current study are available at https://doi. org/10. 25375/ uct. 20495136. Additionally, all isotope data needed to reproduce the U-Th and U-Pb ages and U-Pb isochrons are also available in Supplementary Data 1 Tables  1  and 2 , and all data used to generate Figs. 1  and 4  are also available in Supplementary Tables  1  and 2  and Supplementary Data 1 Table  3.
Acknowledgements Bruno Scaillet acknowledges support from both  LabEx VOLTAIRE  ( LABX-100-01 ) and  EquipEx PLANEX  ( ANR-11-EQPX-0036 ) projects, which made the laboratory work reported in several papers of this special issue possible. He also warmly thanks  François Chabaux  for his supervision of this special issue and  Adenise Lopes  for her efficient help in the editorial processing.