dataesr/scientific-paragraphs-categorization huggingface dataset:
No OTU was common to all oceanic areas investigated here and many were only detected in one sample (Fig. 2a, b ). A few dominant OTUs were shared across oceanic regions (Fig. 2b, c ). For example, the 7 OTUs common to the Mediterranean (PROSOPE and BOUM datasets) and the Barents and the Norwegian Seas (ARCTIC dataset) covered more than 56% of the pufM sequences retrieved from these oceanic biomes (Fig. 2b, c ). Similarly, the 3 OTUs shared by the ARCTIC and MALINA datasets grouped 104 pufM sequences (~20% of sequences; Fig. 2b, c ). OTUs common to at least two oceanic regions, hereafter identified as subcosmopolitan OTUs, were affiliated to αand γ-Proteobacteria within similar proportions (25% and 28%, respectively, Fig. 2a ). In contrast, all OTUs affiliated to β-Proteobacteria were detected in only one oceanic region (Fig.
Discussion Recent results gathered from sampling expeditions (e. g. refs  17, 18, 20  ) and from high-throughput sequencing approaches to achieve pufM gene polymorphism (e. g. refs  17, 19, 25  ) question the actual extent of the diversity but also the existence of biogeographical patterns for AAP bacteria in marine systems. Indeed, (i) most pufM sequences  identified from newly explored ecosystems, including some isolated and extreme environments, are similar to sequences retrieved elsewhere (e. g. refs  17, 18, 20  ), (ii) next generation sequencing approaches such as 454 pyrosequencing  19, 25  or Illumina MiSeq amplicon  17  did not yield a significant higher number of OTUs than classical clone library methods (e. g. refs  15, 16, 26  ). We previously addressed these issues and highlighted the need to rely on comprehensive analyses integrating comparable datasets of pufM sequences from different oceanic regions  20.
Since our analysis was based on a dataset of only 1,306 sequences and four marine regions, we acknowledge that ecoclade identification should be controversial. To determine if these ecoclades have an ecological consistency beyond the oceanic regions investigated here, a set of pufM sequences amplified from surface waters of the Pacific Ocean  16  was added to the primary dataset. Although these pufM sequences were not obtained using the primer set that we used, 76% of them fell in 9 predicted ecoclades (ecoclade No. 1, 11, 12, 14, 17, 27, 35, 38, and 47). These ecoclades are mainly affiliated to Gammaproteobacteria with projected habitats H0 (15%), H3 (46%) and H4 (15%). The moderate to high salinity levels of these projected habitats are consistent with the environmental settings reported by the authors  16.
Methods Brief description of the pufM dataset. The dataset was assembled from studies  15, 18, 20, 35  examining AAP bacterial communities using pufM sequences amplified using the PufMF forward  13  coupled with the PufM_ WAW reverse  44  primers to give a ~245 bp PCR product. For more details on PCR amplification conditions and clone library construction, see Lehours et al. 15. We analyzed a total of 1,306 pufM sequences (see supplemental informations) for which at least one representative sequences of each operational taxonomic unit (OTU) are available in Genbank under accession n° HQ871842-HQ871863, JF421730-JF421749, GQ468944-GQ468986, JN248465-JN248539, and KM654564-KM654598.
amnh. org/open_source/gdmg/download. php). More details on the area sampled, the sampling procedures and the ancillary parameters characterizing each sampling area were described previously  15, 18, 20, 35. The main ancillary parameters characterizing each sampling area, summarized in Table  S1 , were plotted in box plots generated using R software  48  and used to perform a Principal Component Analysis (PCA) generated using FactoMineR package (http://cran. r-project. org/web/packages/FactoMineR/index. html). Sequence clustering into OTU. A conservative value of 94% nucleic acid sequence similarity  49  was chosen for clustering the 1,306 pufM sequences into Operational Taxonomic Units (OTUs) using the furthest neighbor clustering method. Sequence clustering was performed using MOTHUR (http://www.
mothur. org/)  50. MOTHUR was also used to generate a heatmap displaying the relative abundance of each OTU for each station. To compensate for the sequencing depth bias per sample in the heatmap generation, sequence abundance values within each OTU were normalized for comparison of OTU abundance between samples. A clustering, based on OTU composition and abundance (Bray-Curtis distance) at the different stations, was also performed and plotted on top of the heatmap. The Venn diagram was generated using MOTHUR and an "in house" developed Perl script. Phylogenetic analyses of pufM sequences. All pufM sequences were aligned using ARB (http://www. arb-home. de/)  51  , and added using ADD-BY-PARSIMONY algorithm to a robust pufM tree constructed as described previously  15. Phylogenetic tree display and annotation were performed with iTOL software (http://itol.
psb. ugent. be/software/details/ZT)  54. Taxon-based approach and demarcation of "ecoclades". To identify AAP bacterial taxa which may be analogous to the concept of 'indicator species'  24  , tables of relative abundances for phylogroups and for OTUs were constructed. We used the indicator value (IndVal) index, which combines the relative abundance and relative frequency of occurrence of OTUs  55. Multivariate regression trees were computed with the R package mvpart  56  in order to represent the relationship between phylogroup or OTU relative abundances and the environmental matrix. The quantitative environmental parameters used in the MRT were the following: depth, salinity, concentrations in nitrate, phosphate, nitrite, silicate and chlorophyll a, latitude and longitude. The qualitative parameters used in the MRT were: the trophic status of the sampling location (defined according to phosphate concentrations as eutrophic (>20 µg.
L -1 ), mesotrophic (10-20 µg. L -1 ) or oligotrophic (<10 µg. L -1 )); the distance to shore (coastal or offshore), the oceanic region and the sampling depth relative to the DCM (Table  S1 ). We used AdaptML (available at http://almlab. mit. edu/adaptml/)  57 , to demarcate ecoclades in our marine AAP bacteria dataset. AdaptML is a maximum likelihood method that employs a hidden Markov model to learn 'projected habitats' (distribution patterns among environmental categories) and ecologically cohesive 'populations' (groups of related strains sharing the same projected habitat). Our AdaptML analysis used the 5 habitats (C1 to C5) predicted from the MRT analysis. The habitat learning and clustering steps of AdaptML were performed using the default settings.
Acknowledgements We wish to thank the crews of  R/V La Thalassa ,  R/V L' Atalante ,  CCGS Amundsen ,  F/F Johan Hjort  for outstanding shipboard operations during the PROSOPE, BOUM, MALINA, and ARCTIC 2002 cruises, respectively, and chief scientists  H. Claustre ,  T. Moutin ,  M. Babin , and  R. Ingvaldsen  for coordinating these cruises and inviting us.
Data availability. Sequence representatives of each OTU are available in Genbank under accession n° HQ871842-HQ871863, JF421730-JF421749, GQ468944-GQ468986, JN248465-JN248539, and KM654564-KM654598. All sequences, ADAPTML results and OTU cluster file are provided as supplemental material (Supplemental material SI1, Fig. S2 ).
Species Sampling and Molecular Data Sets In order to both establish species relationships and to estimate divergence times within the genus Oxera, the focal ingroup was composed of the 38 recognized species according to the most recent systematic investigations in New Caledonia (Gâteblé unpublished data, available at http://endemia. nc/flore/fiche588), and taxonomical revisions by de  Kok and Mabberley (1999a, 1999b)  for Australasia and Pacific. We added to the data set the sister lineage Hosea, as well as 10 species belonging to the closely related Clerodendrum clade identified in  Yuan et al. (2010). Three more divergent species of Lamiaceae were used as external outgroups (i. e. , Ajuga chamaepitys, Teucrium pyrenaicum, Rotheca sp. Wen 9487; Supplementary Appendix S1a; available on Dryad at https://doi.
org/10. 5061/dryad. mm1ft40). A total of 51 species were used in this sampling, which we refer to as the Oxera data set, including 22 species with previously published sequences (downloaded from GenBank), and 29 species with new sequences generated for this study. This molecular data set consisted of the 12 DNA loci sequenced in  Barrabé et al. (2015). This allowed us to improve 1) the phylogenetic resolution and 2) branch length estimates relative to  Barrabé et al. (2015). All new DNA sequences were generated using the DNA extraction, amplification, and sequencing VOL. 68 VOL. 68 protocols described in  Barrabé et al. (2015). All accessions used in this study are listed in the Supplementary Appendix S1a available on Dryad. For divergence time estimation, we also used two additional alignments composed of four DNA plastid regions (matK, rps16, trnL-F, and trnL-trnF; Supplementary Appendix S2a available on Dryad) from two data sets, with taxon sampling that spanned the Lamiales and Lamiaceae.
The Lamiales data set included: 1) a subset of the Oxera data set (i. e. , five species; Supplementary Appendix S1c available on Dryad); and 2) 177 representatives of various lineages within Lamiales, whose sequences were downloaded from GenBank (Supplementary Appendix S1c available on Dryad). The Lamiaceae data set was thus composed of 1) the aforementioned Oxera subset and 2) 59 taxa representing all major Lamiaceae lineages (downloaded likewise from GenBank; Supplementary Appendix S1b available on Dryad). This large-scale sampling allowed us to incorporate Lamiales and Lamiaceae fossils as calibration points (see below). All DNA alignment matrices used in this study are available on Dryad.
Phylogenetic Inference For the three molecular data sets, phylogenetic inferences were conducted using Bayesian Markov Chain Monte Carlo (MCMC) as implemented in MrBayes v3. 2. 1  (Ronquist et al. 2012 ) based on single-locus and concatenated data sets. Best-fit nucleotide sequence evolution models were identified using jModelTest  (Posada 2008)  based on the Akaike criterion (more details on settings are provided in Supplementary Appendix S2a available on Dryad). The combined data sets were partitioned to allow each locus to possess specific model parameters  (Nylander et al. 2004 ). The methodological approach of the Bayesian MCMC analyses followed that described in  Barrabé et al. (2015)  and the details of parameter settings are provided in Supplementary Appendix S2b available on Dryad.
All analyses were run on the Cyber Infrastructure for Phylogenetic Research cluster (CIPRES; http://www. phylo. org/; last accessed 18 October 2017). The post-burn-in trees resulting from the MCMC stationary phase were used to construct a majority-rule consensus tree and calculate Bayesian posterior probabilities (PPs); clades were considered well-supported when PP values were ≥0. 95). The three resulting consensus trees are available in TreeBASE (ID 23353) and Dryad. In order to check for phylogenetic incongruence between nuclear and plastid loci, we also ran two phylogenetic reconstructions separately for all six concatenated nuclear regions and all six concatenated plastid regions, using the same MrBayes parameter settings and models of nucleotide evolution as above. These two analyses were only applied to the Oxera data set.
Fossil Dating and Divergence Time Estimation We performed a two-step approach to estimate the temporal evolution of Oxera. This allowed us to test the impact of different dating calibrations and taxonomic sampling on divergence time estimates. In the first step, we performed a fossil calibration on the Lamiales and Lamiaceae data sets using fossils described in a recent Lamiaceae molecular dating study  (Yao et al. 2016). We incorporated three Lamiaceae (Melissa, Ocimum, and Stachys) and three Lamiales fossils (Bignoniaceae, Acanthaceae, and Oleaceae) for dating the phylogeny inferred with the Lamiales data set, and two Lamiaceae fossils (Melissa and Ocimum) for dating the phylogeny inferred with the Lamiaceae data set (for further details on the design and parameters of these calibrations, see Supplementary Appendix S2c, available on Dryad and explanations provided inYao et al.
2016). For root calibrations we used divergence times estimated in  Magallón et al. (2015) : 1) the divergence between Lamiales and Gentianales-Solanales for the Lamiales data set and 2) the divergence between Plocospermataceae and other Lamiales for the Lamiaceae data set. In the second step, the divergence time estimate between Rotheca (sp. Wen 9487) and other Lamiaceae recovered during the first step (i. e. , the dating of the Lamiaceae data set) was used as a secondary root calibration point (see Results section) for the Oxera data set. For the three molecular data sets, molecular divergence times were estimated using the Bayesian MCMC approach implemented in BEAST v. 1. 8. 0  (Drummond and Rambaut 2007). DNA regions were combined and partitions were set as in the above Bayesian MCMC analyses (Supplementary Appendix S2c available on Dryad).
An uncorrelated relaxed molecular clock model was selected following a lognormal distribution, and the Birth-Death process implemented for the tree prior. Other details on analyses, calibration and parameter settings are provided in Supplementary Appendix S2c available on Dryad. The post burn-in trees were summarized, and Bayesian PPs, median height (= age estimate), and the 95% highest posterior density heights interval of each node (95% HPD) assessed, using a Maximum Clade Credibility target tree (named as MCCT tree for the Oxera data set) in Treeannotator v. 1. 8. 0  (Drummond and Rambaut 2007). For the Oxera data set a subset of 100 dated trees (RD trees hereafter) were also randomly sampled from the stationary phase to integrate phylogenetic uncertainty in some of the following analyses (see below).
The ML analyses were conducted in the TreePar R package  (Stadler 2011) , using an optimization algorithm to infer past rates of speciation and extinction and their temporal variation. We fitted various diversification models: a pure birth model, a constant birth-death model, several more complex models allowing one to several rate shifts through time (up to 10 shifts), and finally several diversity-dependent models. All models were fitted on the pMCCT tree (see Supplementary Appendix S2d, available on Dryad for further details on parameter settings) and on the RD trees to account for phylogenetic uncertainty. The best-fit diversification model was identified using the corrected Akaike criterion, and a likelihood-ratio test was used for comparing nested pure birth, birth-death, and rate shift models.
Biological, Ecological, and Geographic Range Data sets To identify and disentangle suspected drivers of species diversification in Oxera, we built a data set by compiling data on five major life traits: 1) flower morphology, 2) fruit morphology, 3) life forms, 4) geographical occurrences, and 5) environmental preferences. The flower and fruit morphology (i. e. , organ dimensions, colors, shapes, and textures) were compiled from herbarium and fieldwork observations on organ dimensions, colors, shapes, and textures. Those traits were coded as 13 discrete and three continuous characters for flower morphology, and three discrete and three continuous traits for fruits (Supplementary Appendix S3a, d, and e available on Dryad). The life form data set was composed of a single discrete trait corresponding to the four life forms usually ascribed to Oxera, namely monocaulous, robust liana, slender liana, and shrub/small tree (Supplementary Appendix S3a and b available on Dryad).
Note that no functional or physiological traits related to light requirements or nutrient use strategy were available for Oxera. The geographical distributions of New Caledonian species were retrieved from the databases of the herbaria of Nouméa (NOU, VIROT), the Museum national d'Histoire naturelle of Paris (P, SONNERAT), the University of Zurich (Z), and additional field observations. The geographical coordinates of herbarium specimen records were then databased, error-corrected for distribution, and finally incorporated into a Geographical Information System (GIS) under QGIS 2. 8. 1. For Australasian and Pacific species distributions were assessed from de  Kok and Mabberley (1999b)  and manually added into the same GIS layer. The environmental data set was composed of three variables that best explain plant distributions across New Caledonia  (Jaffré 1993; Morat 1993 ; Supplementary Appendix S3a and c available on Dryad): geological substrates, vegetation types, and elevation.
68 then averaged across geographical occurrences of each species. To identify ecological syndromes among Oxera species, we performed multivariate analyses on the environmental, flower, and fruit data sets. As we used both continuous and discrete traits, we conducted the PCA analyses by using the  Hill and Smith (1976)  principal component method under the ade4 R package  (Chessel et al. 2004 ). This analysis allowed clustering species among pollinator syndromes, dispersal syndromes, and habitat preferences, which we subsequently treated as new discrete traits according to the species clustering (i. e. , the niche data sets; Supplementary Appendix S3f available on Dryad). We posit that the ecological syndrome of a species reflects the ecological niche it occupies  (Johnson 2010 , Pauw 2013).
For the habitat, pollination, and dispersal niches and statistics were estimated using the "fitContinuous" and "phylosig" functions of the geiger and phytools R packages, respectively  (Harmon et al. 2008; Revell 2012). Estimations were performed on the RD trees, and by averaging estimated values for each of the first n axes of each PCA explaining 90% of the cumulative variance. For life form, each statistic was simply averaged through the RD trees using the "fitdiscrete" function (geiger) and the single discrete trait. To reconstruct the evolutionary history of habitat preference, pollination, dispersal niches, and life form, we conducted ancestral state reconstruction analyses. We first assessed ancestral niche states using the "ace" function in the ape R package  (Paradis et al. 2004 ) applied to the pMCCT tree, and the niche and life form data sets.
simmap" function. We subsequently removed the 11 trees from these analyses and used only 89 RD trees. Absolute shift timings were extracted using a custom R-script from all simulations and summarized by plotting the median number of state changes in different time bins of a 0. 5 Myr time-grid. To investigate whether a particular niche state (pollination, dispersal, or habitat) or life-form would have affected clade diversification rates of Oxera, we conducted multi-state trait-based analyses that estimated simultaneously trait-dependent speciation, extinction, and transition rates on a phylogeny and character distribution  (Fitzjohn et al. 2009 ). These were performed using the "make. musse" function under the diversitree R package  (Fitzjohn et al. 2009) , applied to the pMCCT tree, and the niche and life form data sets.
We first fitted 17 models from a null model (rates independent of trait states) to a full model (all rate components dependent of trait states; Supplementary Appendix S4 available on Dryad), conserving the best-fitting using the corrected Akaike criterion. We performed subsequent Bayesian analyses through a MCMC, run for 10,000 generations, seeding them with rate estimates recovered from the previous ML analyses as priors, and discarding the first 1000 generations as burn-in. PP distributions of all parameters were summarized using the diversitree Rpackage. We also fitted the best model and compared it to the second best model across all RD trees to check that model selection was robust to phylogenetic uncertainty.
These geographical variables (areas of all Oxera species, range asymmetries and range overlaps of all Oxera species pairs) are available on Dryad. Age-range correlation analyses were performed using an extended version of the "age. range. correlation" function of the phyloclim R package (Heibl and Calenge 2013; https://github. com/danlwarren/arc-extensions/ blob/master/age. range. correlation. 2. R; last accessed 18 October 2017), applied to our pMCCT and the RD trees. We launched 1000 iterations for the Monte Carlo resampling procedure to create the null hypothesis of no relationship between phylogenetic relatedness and range overlap, range asymmetry, or habitat distance, and tested it. We calculated linear regressions, whose slopes and intercepts indicate speciation mode (allopatric vs. sympatric) or habitat evolution (conservatism vs.
Phylogenetic Inference The Bayesian MCMC analyses of the three species sampling (Lamiales, Lamiaceae, and Oxera data sets) recovered the same following robust phylogenetic relationships (Supplementary Appendices S5-S7 available on Dryad). The sister genera Hosea and Oxera formed a well-supported clade that was sister to the Clerodendrum clade (PP = 1). Analyses based on the Oxera data set provided more resolution and detail on the internal Oxera relationships, which are congruent with the ones established in  Barrabé et al. (2015)  (Supplementary Appendix S5 available on Dryad). The Australasian O. splendida was placed as sister to the New Caledonian radiation (PP = 0. 72), which included all New Caledonian and nested Pacific subclades. We retrieved seven well-supported New Caledonian subclades (PP = 1; Fig.
2a ), namely the oblongifolia, neriifolia, pulchella, baladica, subverticillata, robusta, and sulfurea subclades. A few supported incongruences (PP ≥ 0. 95) were observed between the phylogenetic trees reconstructed separately from the six nuclear loci and from the six plastid loci (Supplementary Appendix S8 available on Dryad), but these incongruencies were all located near the tips (i. e. , between close species). This discordance did not affect the robustness of the seven New Caledonian subclades previously recovered. These minor incongruences underscore the importance of accounting for phylogenetic uncertainty by using the 100 RD trees in most of our evolution and geographical analyses (see Material and Methods section).
Molecular Dating The three molecular BEAST dating analyses provided congruent divergence times for Oxera and relatives (Fig. 2a , Supplementary Appendices S9-S11 available on Dryad), which can thus be considered as a reliable appraisal of colonization dates and tempo of species diversification. Oxera likely emerged during the late Miocene, and the New Caledonian radiation sensu stricto is estimated to have initiated during the early Pliocene. The median divergence time estimates for the stem node of Oxera were 11. 46 Ma (95% HPD = 5. 65-19. 68), 11. 2 Ma (95% HPD = 5. 61-19. 06), and 12. 02 Ma (95% HPD = 6. 21-19. 16), as recovered with the Lamiales, Lamiaceae, and Oxera data sets, respectively (Fig. 2a , Supplementary Appendices S9-S11 available on Dryad). For the crown node, age estimates were 6.
Oxera Diversification The lineage through time plot highlighted a gradual and exponential increase of the number of Oxera lineages through time (Fig. 2a ). The net conservative diversification rates are summarized in Tables  2  and 3. For the New Caledonian radiation, these rates were 0. 2 species/Myr for an extinction of 0. 9 and 1. 04 species/Myr for a null extinction. With respect to per-unit-area and perunit-log(area) they were estimated between 1. 1×10 -5 and 5. 6×10 -5 species/Myr/km 2 , and between 0. 02 and 0. 106 species/Myr/log(km 2 ), respectively. The BAMM analyses inferred two early instances of changes in the diversification rate. The phylorate plot showed an increase in mean diversification rates at the crown node of Oxera and the second deepest node of the Clerodendrum clade, whereas Hosea demonstrated a decrease in these rates (Supplementary Appendix S12a available on Dryad).