dataesr/scientific-paragraphs-categorization huggingface dataset:
9 m 3 s -1. Above this value, the flow is constrained inside a rectangular weir and a weir equation is used to relate water depth and discharge. The water level is currently measured with an ultrasonic sensor (Paratronic US6) and two "Nilomètres" (Serosi, vertical arrays of electrodes that are progressively connected as water level rises) for low and high water stages (sizes 960 and 1920 mm). Note that in the past, different devices were used to measure the water level. A bubbler sensor was mainly used before 1997, and since then, several sensors including US, radar, a home-made sensor called "ELLAN"  (Olivier and Pebay-Peroula, 1995)  and Nilomètre have been used. Water level measurements are recorded with a Serosi data logger with a frequency that is controlled by water level changes. Water level is measured every 10 seconds in summer and every minute in winter, and the data is stored only when it differs from the previous record by more than a given threshold.
The water level is measured with a nilomètre and recorded on a Serosi logger. It is measured every 10 seconds in summer (1 minute in autumn and winter) and the data is recorded only if the change in the water depth since the last measurement exceeds a given threshold (same procedure as the Laval). For the Francon station, the gauging system is a Parshall flume and the water level is measured with an ultrasonic sensor (Paratronic US10) and recorded on a Serosi logger following the same type of procedure as what was described for the Laval. For the Brusquet station, the gauging system is a Parshall flume, and the water level is measured with a nilomètre (1920 mm) located in a well. The acquisition frequency is one point per minute. A V-notch weir with a nilomètre was installed in 2010 to better measure low flows but it was damaged by a flood in 2018.
The Bouinenc station is different from the others since it is located in a natural river section next to a bridge in the village of Draix. Until 2016, the water level was measured with an ultrasonic sensor (Paratronic US10) attached to the bridge. A gauging curve was built to compute the discharge based on several manual gauging with salt dilution. In 2013, the section was greatly modified by a large flood that moved bars around and a new bar appeared just below the US sensor. The gauging relation is therefore out-of-date. There has not been anymore gauging since then hence no discharge data is available after this date.
Measurement Concentration in suspended matter is measured at all the hydrosedimentary stations using a combination of turbidity sensors and automatic samplers. All the stations are equipped with an ISCO automatic sampler, even two for the Laval. Each sampler is able to collect up to 24 one-liter samples. The samplers are controlled by the data logger to collect water (including suspended Moreover, the stations are equipped with sensors for a continuous measurement of turbidimetry. The Laval, Moulin and Francon (until 2018 for Francon) stations are equipped with an optical fiber sensor that was specifically designed for the high concentrations that are encountered in these catchments (several hundreds of g L -1 ;  Bergougnoux et al, 1998). This sensor is able to measure concentrations in the range 10-800 g L -1 with an accuracy of ± 5 g L -1.
Soil temperature at several depths and locations has been monitored since 2004 and related to weathering processes in the marl  (Ariagno et al, 2022). High-resolution repeated Lidar surveys have demonstrated the seasonality of slope erosion processes  (Bechet et al 2016). Detailed measurements of bedload sediment transport have been undertaken with a Birkbeck slot sampler in the Moulin ravine  (Liébault et al, 2016)  and analysed in relation to the seasonality of bedload transport  (Liébault et al, 2022). Instantaneous bedload fluxes recorded by this sampler are amongst the highest reported values in the world, with values commonly exceeding 10 kg m -1 s -1. This bedload dataset also shows a counter clockwise seasonal bedload hysteresis that can be attributed to a yearly sediment pulse reaching the catchment outlet during autumn and early winter, as also documented by scour chain surveys of alluvial deposits.
Water chemistry sampling campaigns have explained the partitioning of water through runoff and subsurface flow (Cras et al 2007), and geochemistry analyses of suspended sediment have quantified their contribution to fossil organic carbon delivery  (Graz et al, 2012). Finally, in-situ CO2 chambers  (Soulet et al, 2018)  have quantified the CO2 emissions due to marl weathering and their dependency on temperature  (Soulet et al, 2021). All of the approaches listed above underline the potentiality of the dataset presented here to contribute to a variety of questions concerning critical zone processes and the interactions between chemical, physical and biotic components in these badlands.
Data availability A snapshot of the full data set presented here is available directly for review at https://doi. org/10. 57745/BEYQFQ  (Klotz et al, 2023). This subset covers years 2015 to 2019 and includes rainfall and meteorological data, as well as discharge and sediment yield data at 4 stations. The full data set with enhanced data services is available in the BDOH database repository at https://doi. org/10. 17180/obs. draix  (Draix-Bleone Observatory, 2015). BDOH database as well as the snapshot files contain data that has been criticized and validated following the procedures that are described above. BDOH web interface provides direct and free access to data for search and visualization. It includes detailed information on the acquisition period and number of data points, data acquisition procedures and sensors, data completeness at the monthly and annual scales and a quick visualization tool that makes it easy for the user to browse through the data set  (Branger et al, 2014).
Note that data download from BDOH requires creating an account, which is free of charge but restricted to the BDOH data policy including noncommercial use of the data. The download interface offers an integrated interpolation/averaging tool that allows exporting the data either with its native resolution or with standard resolutions (for instance, hourly or daily data) useful for modelling purposes. Finally, BDOH database is also continuously updated with recent data, and is able to keep track of possible modifications in gauging relations.
Conclusions We presented a data set of hydrological and sediment fluxes from 6 small mountainous badland catchments of Draix-Bléone Observatory. Data spans up to 40 years, with a particular emphasis on floods that contribute to most of sediment fluxes. Highfrequency rainfall records at 9 locations make it possible to quantify short-period rainfall intensity and analyse rainfall spatial variability. Water discharge measurements provide detailed information on flood dynamics and flashiness. Both suspended load and bedload contributions are measured and indicate intense transport and erosion rates. We also presented the data criticism and validation steps that are performed in order to provide a qualified and usable data for the user.
Acknowledgments Draix-Bléone observatory is supported by the  Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE) , the  Observatoire des Sciences de l'Univers de Grenoble (OSUG) , and the  Institut National des Sciences de l'Univers (CNRS-INSU). It is part of  OZCAR  research infrastructure, which is supported by the  French Ministry of Research, French Research Institutions and Universities. In the early years of the Observatory, the design, construction and maintenance of infrastructures were also supported by  ONF-RTM.
These gills were examined under a Wild Heerbrugg ® M8 binocular. We noted the presence of a single monogenean individual. The parasite specimen was recovered To enable the study of its parasites, the gills of the specimen were stored in 96% ethanol. These gills were examined under a Wild Heerbrugg ® M8 binocular. We noted the presence of a single monogenean individual. The parasite specimen was recovered using an entomological needle and mounted on a slide in a drop of Hoyer's medium  [19]. The slide was covered with a coverslip to flatten the specimen. It was left for 24 h in a horizontal position before sealing the coverslip with glyceel  [20]. Identification was performed using a Leica ® DM 2500 microscope equipped with a digital camera (Leica DMC 4500) and phase contrast. The slide was deposited at the Royal Museum for Central Africa, Tervuren, Belgium (accession number RMCA_VERMES_ 43681).
Funding: A. M. M. ( BOF22BL08 ) and N. K. ( BOF21PD01 ) are funded by the  Special Research Fund of Hasselt University , and M. P. M. V. by the  Special Research Fund (BOF) of Hasselt University  ( BOF20TT06 ,  BOF21INCENT09 ) and by research grant  1513419N  of the  Research Foundation-Flanders (FWO-Vlaanderen ). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
No evidence that the terminal repeats of Meloidogyne contigs are transposable elements Drosophila and other Diptera insects that have lost telomerase have replaced simple telomeric repeats by retro-transposons. Furthermore, previous analyses have suggested transposable elements are active in M. incognita  (Kozlowski et al. , 2021). Therefore, we investigated whether the composite repeats present at some contig extremities in mitotic parthenogenetic Meloidogyne could be related to transposable elements as well. We used the EDTA software  (Ou et al. , 2019)  to predict and annotate transposable and other repetitive elements in the Minc, Mjav and Mare genomes (Supplementary Table  7 ). We checked whether some repetitive elements were predicted in the regions containing the composite repeats we had identified.
We further investigated this case and searched whether additional evidence would support this repeat as being a CACTA DNA transposon. No evidence for a transposase or any of the protein-coding genes usually found in CACTA DNA transposon could be identified in this predicted repeat. Furthermore, searching this annotated repeat (TE00000823) against the Rebase28 database  (Bao et al. , 2015)  returned no significant hit. Hence, this assignment as a CACTA DNA transposon is most likely an annotation error from EDTA. No evidence for a transposase or any other protein-coding gene could also be found in the Minc composite repeat itself, and the sequence returned no hit against Repbase28. The same results were obtained with Mjav and Mare composite repeats. Therefore, no evidence supports any of the identified terminal repeats could be related to a known transposable element.
Stage Motif  found that 9 of the 14 transcripts containing the repeat motifs had at least one isoform that mapped to the M. incognita genome assembly with at least 94% identity on at least 80% of their length. Three other transcripts had mapping isoforms but none respected the coverage and identity threshold and two other transcripts had no isoform mapping the genome (Supplementary Table  8 ). As short-read transcriptome data could be prone to assembly errors on highly repetitive sequences, we also performed the same suite of analyses on M. incognita IsoSeq transcriptome data from mixed developmental stages retrieved from the NCBI (PRJNA787737 SRP350177). We identified 22 iso-seq reads that contained at least one of the three motifs and mapped them to the M. incognita genome assembly (Supplementary Table  9 ).
ONT reads QC and filtering We first used guppy-v6. 0. 6 in super high-accuracy mode with a minimal quality score of 7 (--min_qscore 7) to base-call reads from the raw sequencing signal. Raw sequencing libraries and the configuration files used for the basecalling are described in Supplementary Table  10. We then analyzed the reads quality and length distribution as a quality-check using cONTent, a home-made script available at https://github. com/DjampaKozlowski/cONTent. Following QC, we used nanofilt  (De Coster et al. , 2018)  to crop the 50 first and the 30 last nucleotides as these regions showed reduced per-base quality. We then selected reads that were at least 2 kb long and had a quality score Q > 12. For M. incognita, this returned 1,709,063 higher quality cleaned reads out of a starting number of 6,619,891 raw reads.
We estimated genome completeness using two strategies. First, we used KAT  (Mapleson et al. , 2017)  to estimate how far the diversity of k-mers present in the cleaned short reads was retrieved in the genome assemblies for each species (Supplementary Figure  3 ). Second, we used CEGMA  (Parra et al. , 2007)  and BUSCO  (Manni et al. , 2021)  to estimate which percentage of evolutionarily conserved single-copy genes could be retrieved in the genome assemblies. We used CEGMA version 2. 5 with default parameters to identify eukaryotic evolutionarily conserved genes and their average numbers in the Meloidogyne genomes. We used BUSCO version 5. 4. 4 with the Metazoa odb9 dataset and default parameters to estimate the percentage of widely conserved animal genes retrieved in complete and partial length in the three genomes.
Gene predictions and duplications detection and classification Predictions of gene models in M. incognita, M. javanica, M. arenaria and genomes were done with the fully automated pipeline EuGene-EP version 1. 6. 5  (Sallet et al. , 2019). EuGene has been configured to integrate similarities with known proteins of Caenorhabditis elegans (PRJNA13758) downloaded from Wormbase ParaSite  (Howe et al. , 2017)  as well as the "nematoda" section of UniProtKB/Swiss-Prot library (UniProt  Consortium, 2018) , with the prior exclusion of proteins that were similar to those present in RepBase  (Bao et al. , 2015). We used as transcriptional evidence, transcriptome data for M. incognita, as it is the Meloidogyne species with the most comprehensive expression data available. RNA-seq data from pre-parasitic J2, J2-J3 and adult female stages  (Blanc-Mathieu et al.
, 2017)  were assembled de novo using Trinity  (Haas et al. , 2013)  followed by a cleanup that retains for each trinity locus only the transcript that gives the longest ORF. The dataset of M. incognita assembled transcriptome was aligned on the genomes of the four Meloidogyne species using Gmap  (Wu and Watanabe, 2005)  and except for M. incognita the option "cross-species" was used. Only alignments spanning 30% of the transcript length with at least 97% identity were retained. Statistics of gene predictions in the four species are available in Supplementary Table  1. The EuGene default configuration was edited to set the "preserve" parameter to 1 for all datasets, the "gmap_intron_filter" parameter to 1, the minimum intron length to 35 bp, and to allow the non-canonical donor splice site "GC".
Dataset of nematode genomes and proteomes We collected nematode genome assemblies with a minimal N50 length of 100 kb either at the scaffold or contig level and with predicted protein-coding genes available. We started by the list of sequenced genomes at WormBase ParaSite  (Howe et al. , 2017)  and within a given nematode genus we kept up to three genomes with the highest N50 lengths. Then, we complemented this list with the ensemble of nematode genomes available at the NCBI, using the same criteria for selection (N50 length >100 kb, availability of predicted genes and up to three genomes in a given genus). Our selection included the C. elegans genome and proteome and we did not apply a limitation of 3 species for the Meloidogyne genus, since this was the focal point of our study. Because no gene predictions were available for Meloidogyne luci  (Susič et al.
We set an e-value threshold allowing retrieval in the C. elegans proteome of the query protein and no unrelated proteins. For Trt-1, we used the 'telomerase reverse-transcriptase' PANTHER  (Thomas et al. , 2022)  domain (PTHR12066) with an e-value of 1E-15. Pot-1 presented no specific protein-domain and this domain-based strategy could not be used for this protein. The single-strand telomeric DNA-binding proteins Pot-2, Pot-3 as well as Mrt-1 all possess a 'ssDNA-binding domain of telomere protection protein' Pfam  (Finn et al. , 2016)  domain (PF16686) which was used as a query with an e-value of 1E-15. For Mrt-2, we used the 'Repair protein Rad1/Rec1/Rad17' Pfam domain (PF02144) as a query with an e-value threshold of 1E-40. For the double-strand telomeric DNA-binding proteins Tebp-1 and Tebp-2, we used as query the Panther domain 'GA binding and activating and spk (spk) domain containing-related' (PTHR38627) with an e-value threshold of 1E-10.
Detection of canonical nematode telomere repeats The 68 nematode genomes were scanned for the canonical (TTAGGC)n nematode telomere repeat using the Telomere Identification toolKit Tidk (https://github. com/tolkit/telomeric-identifier). We used the command tidk find with -c nematoda option and a window size of 1000 nucleotides. The C. elegans telomere repeat was considered present if repeated at least 50 times within the 2000 last or first nucleotides of at least 3 contigs. Because repetitive regions might be misassembled in the genomes we also used fuzznuc from the EMBOSS package  (Rice et al. , 2000)  to further search (TTAGGC) 2 dimers anywhere on the genome assemblies. We considered the telomeric repeat possibly present if repeated least 100 times (50 consecutive dimers). Finally, the absence of the canonical (TTAGGC)n repeat may also be due to repeat filtering during the genome assembly process.
Therefore, the canonical telomeric repeat was searched in raw Illumina reads whenever available in SRA. For each species, when available, we chose the SRA data produced with illumina NovaSeq for WGS. We used (TTAGGC) 10 as a query to perform a blastn search on NCBI, using the SRA library corresponding to the species of interest as a subject and deselecting the low complexity regions filter. We considered the telomeric repeat as possibly present when more than 100 matches of (TTAGGC) 10 could be retrieved in the reads. The canonical repeat was considered present in a species whenever evidence from either tidk or from fuzznuc plus blast against SRA could be retrieved. When evidence from fuzznuc was found but no SRA data was available the canonical repeat was considered possibly present. In all other cases, it was considered absent.
Identification of new candidate telomeric repeats Because the canonical (TTAGGC)n telomeric motif was not found in the Meloidgyne genomes, we also searched for clusters of any perfect repeats of sizes 6-12 using the equicktandem and etandem commands from the EMBOSS package  (Rice et al. , 2000). Because no simple tandem repeats of size 6-12 were identified at contig ends, we searched for more complex and possibly degenerated motifs. For each species, we extracted the first and last 2kb of all contigs and searched for frequent motifs using MEME-suite  (Bailey et al. , 2015)  in classic mode on these sequences. Any number of repetitions (anr) mode was selected with iteratively searching motifs from size 50 to 100 with up to 5 different motifs reported. After examination of MAST results from the MEME suite, we realized that two motifs frequently co-occurred and covered almost the whole length of many contig beginnings or ends.
We then only selected those contig beginnings and ends that contained repeats of these two motifs and re-launched a new motif search. This new motif search was with max. 3 motifs with a size range of 80-160. The results of MAST allowed identifying for each species (Minc, Mjav and Mare) a suite of 3 enriched motifs with one motif being conserved in the three species. For each species we considered the suite of 3 motifs as a repeat unit, and extracted all these repeat units in the corresponding genomic regions. We aligned these repeat units using MAFFT v7  (Katoh and Standley, 2013)  with option G-INS-i. The obtained multiple sequence alignment was then used as an input to the EMBOSS  (Rice et al. , 2000)  Cons program to build a consensus. We also retrieved for each enriched motif of each species, the corresponding FASTA sequences from MEME results, built a multiple alignment with MAFFT using the same parameters as for the whole repeat unit and constructed a hmm profile for each motif, using hmm-build from the HMMER package  (Mistry et al.
Confirmation of telomeric position of the identified repeats with FISH Specific primers 5'-TCGTCCATAGGTTCAGGCTT-3' and 5'-GGGTCTACTTGGGTGGGG-3' (Supplementary Fig. 8 ) were designed on the Minc consensus candidate telomere sequence using Primer 3 software  (Untergasser et al. , 2007). Probe for FISH experiment was prepared by PCR labeling with biotin-16-dUTP (Jena BioScience) using M. incognita genomic DNA as template. PCR reaction was prepared in 25 µL volume containing 1x Colorless GoTaq Flexi Buffer, 2. 5 mM MgCl2, 0. 1 mM dNTPs, 0. 4 µM primers, 1. 25 U of GoTaq DNA Polymerase (Promega) and 0. 02 ng of gDNA. For PCR settings 3 min at 95 °C of initial denaturation was followed by 35 amplification cycles (20 s at 95 °C, 20 s at 62 °C and 40 s at 72 °C) and 5 min at 72 °C for final extension.
G4-quadruplex prediction We used the G4-Hunter software  (Brázda et al. , 2019)  with a window size of 25 and a minimal score of 1. 2 to detect regions possibly forming G4-quadruplexes on the composite terminal repeats as well as the whole genome sequences of the three Meloidogyne species. Using an in-house script, we retrieved only the non-overlapping positions, distant by more than 25 bp, and the score for each G4-quadruplex position, and we plotted their frequency using Rstudio.
Transcriptomic support of Minc telomeric repeats We retrieved M. incognita RNA-seq Illumina data of four developmental life stages (eggs, pre-parasitic J2, J3-J4 and adult female) from a previous publication  (Blanc-Mathieu et al. , 2017). For each developmental life stage, we pooled the triplicates and performed a de novo transcriptome assembly using Trinity-v2. 4. 0  (Haas et al. , 2013). We used nhmmer  (Mistry et al. , 2013)  with the hmm profiles of each Minc motif as queries to identify assembled transcripts and isoforms containing one or several of these motifs. We repeated the same nhmmer search on an Iso-seq mixed-stage Minc transcriptome downloaded from the NCBI (PRJNA787737 SRP350177). Assembled transcripts as well as Iso-seq reads that contain one or several telomeric motifs were aligned on the M.
Acknowledgment We are grateful to the genotoul bioinformatics platform  Toulouse Occitanie (Bioinfo Genotoul , https://doi. org/10. 15454/1. 5572369328961167E12) for providing computing resources. We are grateful to the bioinformatics and genomics platform, BIG,  Sophia Antipolis  ( ISC PlantBIOs , https://doi. org/10. 15454/qyey-ar89) for computing and storage resources. We would like to thank  Marine Poullet ,  Julia Truch ,  Philippe Castagnone-Sereno ,  Pierre Abad , and  Claire Caravel  for help, support and stimulating discussions. We are grateful to  Paulo Vieira  and  Sebastian Eves-van den Akker  for providing early access to the genome and predicted proteins of Pratylenchus penetrans. This work was supported by the  French government , through the  UCAJEDI Investments  in the Future project managed by the  National Research Agency (ANR)  under reference number  ANR-15-IDEX-01.
Data availability All the raw long and short genome sequencing reads for the three species have been deposited in the EBI's European Nucleotide Archive (ENA) under BioProject PRJEB61149 with detail of each library and accession numbers in Supplementary Tables  10  and 11. Genome assemblies and annotations have been deposited in the French national data repository 'Recherche Data Gouv' and will be available upon publication of the paper in a peer-reviewed journal.