dataesr/scientific-paragraphs-categorization huggingface dataset:
RECORDS FROM THE TIDE GAUGE DATA MAINTAINED BY HAWAII UNIVERSITY AND THE UPF TIDE GAUGE IN MANGAREVA Currently, the tide gauge of the University of Hawaii hosts three different instruments: A FLOAT sensor with an encoder, a PRESSURE gauge and a RADAR altimeter. The dataset covers the period 2008/07-2021/04. The sampling rate is 5 min for the FLOAT sensor and 1 min for the two other sensors. We found that the PRESSURE sensor was badly perturbed between 2012 and 2019, so we ignored these measurements. The results of the FLOAT sensor and the RADAR are in very good agreement. There is no difference in amplitude with the results of the UPF RADAR but only a slight phase difference of 1° in the semidiurnal band. The nontidal variations are also in perfect agreement (Figure  8 ), as indicated also by the differences between sensors shown in Figure  9.
The unusual event at the beginning of 2018 disappears on this graph. This clearly indicates that it was a real signal. The difference between the sensor measurements is of the order of 30 mm peak to peak at short periods. There is also a slight differential drift especially at the beginning of the float sensor record. A linear regression between the different datasets gives: RADAR UH = 1. 0025 ± 0. 0002*RADAR UPF (correlation coefficient r = 0. 999). RADAR UH = 0. 9999 ± 0. 0002*FLOAT UH (correlation coefficient r = 0. 999). There is only a 0. 3% calibration difference between the UPF and the UH RADAR measurements. The UH FLOAT sensor calibration agrees with the UH RADAR calibration. Thanks to the long period of nearly 13 years covered by the University of Hawaii tide gauges in Mangareva, it was possible to determine a secular trend, as the drift of the RADAR and of the FLOAT sensor are very similar.
| CONCLUSIONS This study provides cleaned, calibrated and with a verified time-tagging of sea-level data for the five tide gauge geodetic stations installed in French Polynesia (see Figure  1 ) for the period 2009-2020. For preprocessing and analysis of the data, a three-level operational database was set up: • LEVEL 1 raw data with original sampling rate, • LEVEL 2 corrected data with original sampling rate, • LEVEL 3 hourly averaged data and tidal analysis residues. The database, entitled 'SEA LEVEL collected from TIDE STATIONS in South Pacific Ocean from 2009-06-13 to 2021-01-28', can be accessed on the NOAA National Centers for Environmental Information (NCEI) data servers as 'NCEI Accession 0244182' and contains two subsets: The first one is relative to the original sampling rate (LEVEL1 and LEVEL2) and the second one (LEVEL3) is relative to the hourly re-sampling.
The harmonic tide model coefficients derived from the analysis of the hourly data subset are also provided for each tide gauge station. The RADAR and PRESSURE gauge measurements of the five UPF/OGT tide stations have been both validated for the precise measurement of the tides and short-term phenomena such as tsunami waves. The RADAR dataset is the only one suitable for long-term analysis of Mean Sea Level (MSL) variations (see Figure  6 ). Of course, as who can do more can do less, RADAR measurements are also suitable for the study of short-term phenomena. A metrological modelling of the absolute variations of the Mean Sea Level (ΔMSL) requires the establishment of a common datum for the five tide gauges with respect to a reference ellipsoid (through GNSS positioning), as well as the modelling of long-term fluctuations affecting measurements, whether of instrumental or geophysical origin (meteorological, subsidence of the islands Δh).
In Mangareva, the 2017 data records are missing in both the UPF and IOC databases. 6 ). Δh value reported by Martinez-Asensio et al. is -1. 0 ± 0. 4 mm/year. The absolute trend in sea level ΔMSL from 1993 to 2019 using observations from satellite altimeters for this site is estimated at 2. 76 ± 1. 18 mm per year (GFSC, 2021). In conclusion, there is a reasonable agreement between the sea-level rate of change determined with satellite altimetry and our result in Vairao and in Mangareva. Our values are larger in Tubuai and particularly in Rangiroa, but these datasets are less reliable as they present large interruptions.
A B L E 1 Location of the geodetic tide gauges in French Polynesia managed by the Geodesy Observatory of Tahiti/UPF. We also mentioned the tide gauge of the University of Hawaii (Rikitea UH), which was used for comparison purposes (see Section 7) Downloaded from https://rmets. onlinelibrary. wiley. com/doi/10. 1002/gdj3. 172 by EVIDENCE AID -BELGIUM, Wiley Online Library on [27/02/2023]. See the Terms and Conditions (https://onlinelibrary. wiley. com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 4 | DATA VALIDATION AND.
Downloaded from https://rmets. onlinelibrary. wiley. com/doi/10. 1002/gdj3. 172 by EVIDENCE AID -BELGIUM, Wiley Online Library on [27/02/2023]. See the Terms and Conditions (https://onlinelibrary. wiley. com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License provides a very coherent result, RSL = 518. 0 ± 1. 2 mm and ΔRSL = +36 ± 3 mm, with m0 = 50 mm. At Tubuai, the results obtained with a first dataset (2010-2014, sampling rate 2 min) and a second one (2015-2020, sampling rate 1 min), after an interruption of 14 months, are coherent within the associated 2σ errorrange for what concerns the tidal signal, but an increase of 40 mm of the apparent RSL (Table.
ACKNOWLEDGEMENTS List of successive Chief Officers of the local outposts of  SHOM in French Polynesia ('Chefs de la base hydrographique de la Polynésie  française'). We thank all of them for their dedication in the maintenance of the network of the tide gauges: • Yann Dupont (2007)(2008)(2009). • Yves Marie Tanguy  (2009)(2010)(2011). • Marie Protat  ( 2011-2013 ). •  Julien Simon  (2013Simon ( -2015)). • Régis Coindet ( 2015-2018 ). • François Becquet de Mégille  ( 2018-2020 ). •  Julien Lagadec  ( 2020-2022 ).
FUNDING INFORMATION We acknowledge many sources of funding over the years from several institutions belonging to the central government of France (CNRS, CNES, ANR, SHOM, Ministère de l'Outre-Mer, Fonds Pacifique) and the local authorities of French Polynesia (UPF, Haut-Commissariat de la République, local government of French Polynesia). We thank NOAA for the permission to use the transmission channels of the GOES satellites and for the time spent in evaluating the datasets presented in this article.
T A B L E 1 Location of the geodetic tide gauges in French Polynesia managed by the Geodesy Observatory of Tahiti/UPF. We also mentioned the tide gauge of the University of Hawaii (Rikitea UH), which was used for comparison purposes (see Section 7) Downloaded from https://rmets. onlinelibrary. wiley. com/doi/10. 1002/gdj3. 172 by EVIDENCE AID -BELGIUM, Wiley Online Library on [27/02/2023]. See the Terms and Conditions (https://onlinelibrary. wiley. com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 4 | DATA VALIDATION AND.
20496060, 0 , 0 Downloaded from https://rmets. onlinelibrary. wiley. com/doi/10. 1002/gdj3. 172 by EVIDENCE AID -BELGIUM, Wiley Online Library on [27/02/2023]. See the Terms and Conditions (https://onlinelibrary. wiley. com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License provides a very coherent result, RSL = 518. 0 ± 1. 2 mm and ΔRSL = +36 ± 3 mm, with m0 = 50 mm. At Tubuai, the results obtained with a first dataset (2010-2014, sampling rate 2 min) and a second one (2015-2020, sampling rate 1 min), after an interruption of 14 months, are coherent within the associated 2σ errorrange for what concerns the tidal signal, but an increase of 40 mm of the apparent RSL (Table.
g. Hellman et al. , 2009; Hicks, 1992; Hicks & Birks, 1996). The comparative approach builds upon databases of modern pollen assemblages from traditional agricultural landscapes and compares them with fossil assemblages (e. g. Gaillard et al. , 1994; Mazier et al. , 2006 Mazier et al. , , 2009)). For instance, the indicator species approach has been applied within Britain and Ireland to infer Mesolithic forest manipulation, including identification of secondary woodland taxa following disturbance  (Warren et al. , 2014)  and open ground indicators (ibid. ; Bishop et al. , 2015). Interpretation of such pollen evidence generally relies on the context of certain pollen assemblage and several lines of evidence within the pollen record, including decreases of tree taxa characteristic of mature woodland followed by sudden, regular occurrence or increases of pollen from other tree taxa and woodland herbs favoured by clearance during a short period.
These types of evidence were associated with archaeological records of human activity within and around sites, and therefore these burning events were interpreted as human-induced fire episodes  (Bos & Urz, 2003; Gumiński & Michniewicz, 2003; Hjelle & Lødøen, 2017; Hörnberg et al. , 2006; Kaal et al. , 2013; Mellars & Dark, 1998; Milner et al. , 2018; Woldring et al. , 2012). As we can see, one type of evidence (pollen spectra) dominates in such studies; in fact, the data from the Lahn valley is outstanding because more types of proxies were related to human-induced burning there. Therefore, this case study is     Bos and Urz (2003). Archaeological sites from the Lahn valley area in Germany were investigated at a high chronological resolution. Niederweimar 6 (NW6) and Niederweimar 8 (NW8) are two early Mesolithic archaeological sites discovered in 1994 during gravel mining.
They are both located on river terraces along Holocene residual channels. Lithics and carbonised animal teeth were found within NW8, and a Mesolithic campsite was identified within NW6 where concentrations of artefacts and a fireplace were found. Geomorphological and palaeobotanical research was conducted in conjunction with pollen analysis and radiocarbon dating to reconstruct vegetation transformations in this area. Plant microfossils were collected from different well defined and dated residual channel fills, and pollen data was collected from three sediment profiles along a transect at different distances (75-200 m) from the archaeological sites. Pollen samples were taken from palaeochannel fills of the river Lahn. Charcoal concentrations and NAP totals were calculated. Nineteen samples were AMS dated to obtain a chronostratigraphical framework which covers the period between 11,640 BP and 8,830 BP.
Terrestrial structures have not been discovered in Europe yet. An example of a study in which a link has been made to huntergatherer activity for terrestrial animals without the presence of special constructions is the North Gill site in England  (Innes & Blackford, 2003). There are several exposed peat sections at the site, the base of which is rich in charcoal and contains evidence of fire disturbance. One of the previously defined basal disturbance phases at the site was studied via analysis of fungal spores in conjunction with alreadypublished charcoal and pollen counts. Samples were extracted from the basal disturbance phase at core North Gill 5B. Fungal spores were counted from the same slides as for the pollen and charcoal data derived from the basal disturbance phase at core North Gill 5B.
programme within the  TERRANOVA  project, No  813904 , and supported by the  Liveable Planet programme of Leiden University. The paper reflects the views only of the authors, and the  European Union  cannot be held responsible for any use which may be made of the information contained therein. Jens-Christian Svenning considers this work a contribution to his VILLUM Investigator project " Biodiversity Dynamics in a Changing World " funded by  VILLUM FONDEN  (grant  16549 ). We would like to thank  Prof. Jan Kolen  and  Prof. Corrie Bakels  ( Leiden University, Leiden, the Netherlands ) for inspiring discussions.
The dissolved CO 2 from well F1 was recalculated under PhreeqC software by inverse modeling from the analysis of cations and anions to obtain the maximum values of 30%  (Petit et al. , 2021). Wells F2 and F3 farther from the injection well showed a lower rise with a wider peak. Dissolved CO 2 increases to 3. 54% between 20 and 60 h in well F2. It rises to 3. 67% between 40 and 120 h in the well F3. The CO 2 probe initially installed in well F1 was moved to well F8 from 145 h after the plume of CO 2 had dissipated in F1. Therefore, there are no data for the F8 well before 145 h. The sudden decrease occurring at this time corresponds to the withdrawal and re-filling of the probe. The arrival of CO 2 occurred between 320 and 340 h after the start of the injection. The ORP recording showed minimal values in the F1 injection well while the other wells did not show significant variations after the injection.
Well F2 is only equipped with a CO 2 probe. Alkalinity (as HCO 3 -; mg/L) were measured in the laboratory by the Inflection Point Titration Method. The injection started at t = 0 and lasting 1. 5 h. For a better visibility, data for the conductivity, dissolved CO 2, and pH from well F1 have been added on a second y-axis on the right of the graph. The CO 2 probe initially installed in well F1 was moved to well F8 from 145 h after the plume of CO 2 had dissipated in F1. Therefore, there are no data for the F8 well before 145 h. The sudden decrease occurring at this time corresponds to the withdrawal and re-filling of the probe. The axis F1 to F8 is parallel to the flow direction of the aquifer (Fig. 1 ). Waters samples were collected at 25 cm under the water table (i. e. 61. 10 m NGF for the well F1).
Acknowledgments This research was conducted within the  Aquifer CO 2 -Leak Project  and we thank the entire Aquifer CO 2 -Leak Project team. This project is funded by the  ADEME , the  New Aquitaine region and Carnot ISIFOR , France. The authors are grateful to research  G&E  ( EA 4592 ),  Bordeaux INP , and  University Bordeaux Montaigne  for creating a supportive and exciting research environment. The authors are grateful to the  laboratory EPOC (Talence, France ) and more particularly  Alexandra Coynel , and  Cécile Bossy  from the  M&M platform "Majeurs et Métaux traces " to have permitted the analysis of several samples and to the  ENSCBP laboratory (Pessac, France)  for the XRD analysis. The authors thank the reviewers for their useful comments, their valuable time and their expertise.
Cells were measured on SEM digital micrographs using ImageJ software  (Rasband, 1997). Depth corresponds to dorso-ventral length (DV) and height to antero-posterior (AP) length. SEM images were presented on a uniform background using GNU Image Manipulation Program v. 2. 10. 18. For dissection of thecal plates, isolated cells were placed in a small drop of water on a slide, covered with a coverslip, and a drop of sodium hypochlorite (5% final concentration) was deposited on the border. The coverslip was then gently pressed using a stick and dissociated thecal plates were observed at high magnification using a BX41 (Olympus, Tokyo, Japan) upright microscope equipped with DIC optics. The terminology used for thecal plates in this paper follows the hybrid system of  Hoppenrath et al. (2014)  and  Norris et al.
Sequences alignment and phylogenetic analyses Ostreopsis sequences of the LSU D1-D3, D8-10 and additionally ITS region for morphotype 4 acquired in the present study were used in a multi-loci phylogenetic analy-sis, following the most recent taxonomic treatment of gonyaulaceans by  Tillmann et al. (2021) , and including sequences of the three genera encompassed in subfamily Ostreopsidoideae Gottschling, Tillmann and Elbrächter. For that purpose, 138 sequences of Ostreopsis spp. , Coolia spp. and Alexandrium spp. from the analysis by  Tillmann et al. (2021)  served as a basis to construct our matrix, using Triadinium polyedricum (2 sequences) and Pyrodinium bahamense (3 sequences) as outgroup. Sequences acquired on 25 different specimens in the present study and 21 Ostreopsis spp. sequences retrieved from GenBank were added to complete the genus diversity.
Full voucher information of the systematically representative set comprising 184 gonyaulacean Ostreopsidoideae (84 Ostreopsis spp. , 30 Coolia spp. , 70 Alexandrium spp. ) and outgroup (2 Gambierdiscoideae Fensome, F. J. R. Taylor, G. Norris, Sarjeant, Wharton & G. L. William, 3 Pyrodinioideae F. J. R. Taylor, G. Norris, Sarjeant, Wharton & G. L. William) are provided in Table  S2. As described in  Tillmann et al. (2021) , for alignment constitution, separate matrices of the rRNA operon (i. e. SSU, ITS region and LSU) were constructed, aligned using MAFFT v. 7  (Katoh and Standley, 2013)  and concatenated afterwards using Seaview v. 5. 05 software  (Gouy et al. , 2010). After concatenation, the matrix was refined by eye with Linux version of MEGA software v. 10. 1. 7  (Kumar et al. , 2018).
A second dataset was prepared to analyse the phylogenetic position of the parasitoid Amoebophrya sp. infecting some Ostreopsis specimens. A matrix including small subunit of ribosomal RNA (SSU) and internal transcribed spacer 1 was prepared, using closely related sequences retrieved in GenBank, some sequences covering only SSU. They were aligned with MUSCLE algorithm  (Edgar, 2004 ) followed by refinement by eye. Prior to phylogenetic analyses, jModeltest2 v. 2. 1. 7 (Darriba et al. , 2012)  was used to search for the most appropriate model of sequence evolution. Two methods of phylogenetic reconstruction were used. Maximum Likelihood analysis (ML) was performed using PHY-ML v. 3 software  (Guindon et al. , 2010) , and a bootstrap analysis (500 pseudoreplicates) were to assess the relative robustness of branches of the ML tree.
Phylogenetic analysis For the phylogenetic analysis of Ostreopsidoideae, the alignment comprised 189 OTUs including 25 specimens from Guadeloupe Island (Fig. 7A-O  (Figs. 8, S2 ). Among Ostreopsis, 13 major lineages that corresponded to established taxa at species rank were resolved and well to fully supported (Fig. 8 ):O. cf. ovata, O. rhodesiae, O. mascarenensis, O. fattorussoi, O. lenticularis, O. siamensis, O. heptagona and Ostreopsis sp. 1/2-4, 7-9 (Fig. 8 ). Sequences acquired from the four different morphotypes in the present study (Fig. 7A-O ) were resolved within four major clades (Fig. 8 ). One sequence was recovered in O. cf. ovata clade, 11 in O. lenticularis clade, 6 in O. siamensis clade, and 7 in O. heptagona clade. Sequences of O. cf. ovata, O. lenticularis and O. siamensis from Guadeloupe Island were closely related to sequences already available in GenBank and thus represent known genotypes (Fig.
8 ). Within O. lenticularis clade, all sequences from Guadeloupe Island were closely related to those from French Polynesia (type locality) (Fig. 8 ). Among sequences of O. siamensis, the 6 sequences from the present study were resolved with a strong support with sequences from the Gulf of Thailand (TF25OS, VNPQ218) and Tahiti Island (PNA19-6, PNA19-8 and IFR20-173). By contrast, sequences of O. heptagona were all similar and clustered in a new clade, sister of all other Ostreopsis lineages, which did not include any sequence from GenBank (Fig. 8 ). This clade was basal to all other Ostreopsis sequences but it was fully recovered within Ostreopsis genus based on the concatenated analysis (100BS, 1. 00PP). Phylogenetic analyses inferred from single locus sequences (ITS and LSU D1-D3 + D8-D10) are given in supplementary figures S3 and S4.
(accession numbers MW363873-MW363876) were identical. In the ML-tree (Fig. 10 ), they were resolved with strong support with the sequence MK752531. 1 of an isolate (AT5) for which the host was not identified. From the phylogenetic analysis, it appeared that among the great genetic diversity within Amoebophrya, the parasitoid identified in this study belongs to a clade distantly related to other genotypes known to infect other planktonic dinoflagellates genera such as Akashiwo, Alexandrium, Ceratium (=Tripos), Cochlodinium, Dinophysis, Gonyaulax, Gymnodinium, Karlodinium, Phalacroma, Prorocentrum and Scrippsiella (Fig. 10 ).
Phylogeny and species identities Results from morphotype observations and phylogenetic analysis confirm the presence of four Ostreopsis species in the samples studied from Guadeloupe Island. The concatenated tree reveals a similar topology than found in the recent study by  Tillmann et al. (2021) , and Ostreopsis is a well resolved genus among subfamily Ostreopsidoideae. Within Ostreopsis clade, the topology is also congruent with previous studies based on single locus data (e. g. Chomérat et al. , 2019b Chomérat et al. , , 2020b;; Sato et al. , 2011; Tawong et al. , 2014)  and using a longer dataset provides a stronger support for several clades. While three of the genotypes from Guadeloupe Island cluster unambiguously within already known clades of Ostreopsis (O. cf. ovata; O. lenticularis and O.
(2019). Hence, this confirms that this species possesses a few small pores, as in other species such as O. lenticularis   (Fukuyo, 1981; Chomérat et al. , 2019b) , O. rhodesiae  (Verma et al. , 2016)  or in O. siamensis  (Chomérat et al. , 2020b; Nguyen-Ngoc et al. , 2021). These small pores are however rare and quite difficult to observe, and they may be present in certain strains only, which may explain the variability reported in different studies (e. g. Hoppenrath et al. , 2014). Genetically, the unique sequence from Guadeloupe is not identical with any strain from GenBank and it might constitute a different ribotype. Cells of morphotype 2 identified as O. lenticularis have the typical morphology of this large species, with wide and sometimes almost round cells. The size variation observed in specimens from Guadeloupe is larger than reported in any other study, exceeding the ranges 60-100 mm in depth and 45-80 mm in width given by  Fukuyo (1981)  in the original description.
Diversity and comparison with data from the Caribbean As discussed previously by  Chomérat et al. (2019b) , several confusions have been made regarding O. siamensis and O. lenticularis in different studies, and in most reports the correct identification was not ascertained. For instance, the name change from O. siamensis in  Carlson (1984)  to O. lenticularis in  Carlson and Tindall (1985)  in the interpretation of the same dataset introduced some confusions which have been encouraged by the speculative statement by  Norris et al. (1985)  who considered the two species as possibly conspecific without any detailed argument. Some subsequent reports from the Caribbean area (e. g. Ballantine et al. , 1985; Tosteson et al. , 1986 Tosteson et al. , , 1989) )  do not provide a clear identification of Ostreopsis species and the identity of the studied species remains in question.
1985)  needs to be re-evaluated. Species identification is hardly possible by light microscopy due to large variations in size. Poor distinctive morphological characters lead to considerable confusions in the past and the use of new identification tools based on molecular data appears to be essential for ecological studies and monitoring purposes. This work is however essential to generate a reference dataset of sequences, which constitutes a prerequisite for further development of molecular techniques based on environmental DNA such as probes for fluorescent in situ hydridization assay  (Pitz et al. , 2021) , RT-PCR assays and metabarcoding analyses. While light microscopic observations can accurately estimate the abundance of the genus Ostreopsis  (Boisnoir et al. , 2018 (Boisnoir et al.