dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2020)  based on fifty-year averages  extracted from the WorldClim database (resolution 1 km², www. world clim. org, Hijmans et al. , 2005). Data and methods used by  Marin et al. (2020)  to establish these strata are freely accessible on the ZENODO [Open Aire EU official] repository: https://zenodo. org/recor d/5503746. Seed families used in this experiment were not sampled directly in the wild but produced by two successive generations of parental plants that were germinated in controlled conditions and grown in a common garden environment (see Figure  S2  and associated text for the detailed cultivation protocol and conditions). Only the first parental generation of plants was germinated from seeds collected from field populations on mature plants. These two generations of plants regenerated before our experiment reduced potential maternal environmental effects differentially affecting populations that could have otherwise biased the trait values recorded during the experiments presented here.
We checked that the results were consistent across populations originating from a same elevation (Figures  S5  and S6 ). Finally, we compared whether the 'local vs foreign' results were implying a similar signal of adaptation, maladaptation or their lack thereof in different microhabitats in order to evaluate the reproducibility. All statistical analyses were performed using the R. 3. 5. 0 software (R Core Team, 2018). All generalized mixed models were implemented in R via the glmmTMB R-package  (Brooks et al. , 2017). Assumptions of models (e. g. heteroscedasticity, over-or underdispersion, significance of outliers) were checked both visually and by using the DHARMa R-package  (Hartig, 2020). The models for the time to germination in A. m. pseudomajus violated uniformity of residuals assumptions according to DHARMa analysis.
DATA AVA I L A B I L I T Y S TAT E M E N T Code and data for producing figures and results in this paper are openly available on ZENODO [Open Aire EU official] repository: https://zenodo. org/recor d/5503746. O RCI D Benoit Pujol https://orcid. org/0000-0001-9703-6760 R E FE R E N C E S Andalo, C. , Cruzan, M. B. , Cazettes, C. , Pujol, B. , Burrus, M. , & Thébaud, C. (2010). Post-pollination barriers do not explain the persistence of two distinct Antirrhinum subspecies with parapatric distribution.
Read mapping and sequence alignments The reads of the sequencing output (. fastq) were trimmed using Trimmomatic  (Bolger et al. , 2014)  to remove reads with a quality score below 30 and reads that had any 4-bp window below 30, retaining reads with at least 36 bp  (LEADING: 30 TRAILING: 230 SLIDING WINDOW:4:30 MINLEN:36). The MINLENGTH setting was also used with length set to 36 to remove shorter reads that might not be uniquely positionable against other sequences. Paired reads and combined unpaired reads were used to recover target sequences using HybPiper version 1. 3  (Johnson et al. , 2016)  using a target file available at https://github. com/mossm atter s/Angio sperm s353. Reads were mapped to de-gapped medoid sequences using BLASTX  (Camacho et al. , 2009) , each gene was assembled de novo using SPAdes  (Bankevich et al.
, 2012) , and coding sequences were extracted using Exonerate  (Slater and Birney, 2005). HybPiper was run using the BLAST option  (Altschul et al. , 1990)  because it has been found to produce longer sequences  (Murphy et al. , 2020). Noncoding sequences (i. e. , introns and untranslated regions [UTRs]) flanking the coding sequences were recovered using the script intronerate. py available with HybPiper. Gene matrices were aligned separately using MAFFT V7 (mafft-7. 419-gcc_fc6. x86), with accuracyoriented methods (--localpair --maxiterate 1000) and the option to generate reverse complement sequences to align them together with the remaining sequences based on 6-mer counting (--adjustdirectionaccurately). Matrices were subsequently trimmed using phyutility (https://github. com/black rim/phyut ility) to delete sites that were missing 80% data (-clean 0.
Biogeographical patterns Ancestral range estimation for Cunoniaceae was performed using the dispersal-extinction cladogenesis (DEC)  (Ree and Smith, 2008)  and DEC+J models as implemented in the R package BIOGEOBEARS  (Matzke, 2013). Geographic areas, as defined by  Buerki et al. (2011) , were used with the addition of Antarctica as one of the available regions because of its potential role in the past as a dispersal route for plants and animals (de la  Estrella et al. , 2017 Estrella et al. , , 2019)). The adopted area of delimitation approximates that of  Buerki et al. (2009)   2019 ) were employed here because the oldest one, 160-125 Ma, is older than the time spanned by the current analysis (i. e. , 100. 2 Ma). We performed these biogeographical analyses including and excluding Antarctica as an area to ascertain its impact on the estimation of the biogeographical patterns.
ACKNOWLEDGMENTS We thank  Rafaël Govaerts  for advice regarding the termination of section names and  Heather Lindon  for other nomenclatural advice. We thank  Julia Buckley ,  Craig Brough , and  Tracy Wells , and  Archivo del Real Jardín Botánico, CSIC  for supplying images for Fig. 1 and for information about the artists, and  Karine Gotty  for editing the plate. This work was funded by grants from the  Calleva Foundation  and the  Sackler Trust  to the Plant and Fungal Tree of Life Project (PAFTOL) at the  Royal Botanic Gardens, Kew. We thank  Andrew Thornhill  and an anonymous reviewer for critical comments on an earlier version of the manuscript.
AGO and DCL genes have been analyzed in the Andean G19833 genotype leading to the identification of 15 PvAGO genes and 6 PvDCL genes  [32]. Consequently, except for the report of de Sousa Cardoso et al. [32] , our knowledge of the RNA silencing mechanism in common bean remains quite poor. The aims of this study were to identify and characterize, by in silico analysis, the genes involved in RNA silencing, including AGO, DCL, RDR, DRB, NRPD1, NRPE1, and NRPD2/NRPE2 in common bean. Taking advantage of the availability of two genome assemblies of contrasting origins (Andean and Mesoamerican), we wanted to address the evolution of these genes on a short time scale. Their expression patterns were investigated in different organs using online data and after infection with the fungus C. lindemuthianum by quantitative RT-PCR.
Common Bean Genome Sequence Databases and Annotation Data G19833 (v1. 0) and BAT93 (v10) P. vulgaris genome assemblies and annotation data were downloaded from Phytozome (v10. 0) (http://www. phytozome. net/, accessed on 1 December 2020) and from BAT93 genome data repository  [31]  (http://denovo. cnag. cat/ genomes/bean/, accessed on 1 December 2020), respectively.
Identification of Argonaute, Dicer-like, RDR, DRB, NRPD1, NRPE1, and NRPD2 Genes in Common Bean Genomes In order to identify DCL, AGO, RDR, DRB, NRPD1, NRPE1, NRPD2 genes, tBLASTn  [33]  search was performed on the G19833 and BAT93 genome sequences with the published Arabidopsis DCL  [34] , AGO  [17] , RDR  [15] , DRB  [15] , NRPD1, NRPE1, and NRPD2  [35]  gene sequences as queries, using a cut-off E-value of 1e-10. Gene structure was determined by integrating evidence in the Artemis annotation platform  [36] , including (1) Genemark. hmm ab initio gene prediction  [37] , (2) Glycine max and P. vulgaris ESTs available from Genbank, aligned on the genomes using Sim4  [38] , (3) similarities to protein sequences identified using BLASTx  [33]  on G. max (Wm82. a2v1) from Phytozome (v10. 0) and Arabidopsis (TAIRv10) (https://www.
arabidopsis. org, accessed on 1 December 2020), (4) contigs resulting from G19833 RNA-seq velvet assembly  [30, 39]  aligned on both G19833 and BAT93 genomes using Sim4  [38]. Finally, the Pfam database (http://pfam. xfam. org/, accessed on 1 December 2020) was used to confirm each candidate gene by checking the presence of the typical domain of each family. DCL proteins should have an N-terminal helicase domain (DExD/H-box and helicase-C subdomains) followed by DUF283 (domain of unknown function, known also as Dicer dimerization domain), PAZ (Piwi-Argonaute-Zwille), tandem RNase III domains, and one or two C-terminal double-stranded RNA binding domains (dsRBDs)  [14]. AGOs should have PAZ, MID (middle), and PIWI domains. RDRs should have a conserved RDRP domain. DRB proteins should have two double-stranded RNA binding motif domains.
truncatula  [14] , and RDR and DRB1 [also known as HYPONASTIC LEAVES 1 (HYL1)] sequences from soybean  [15]. The location of each PvA_AGO, PvA_DCL, PvA_RDR, PvA_DRB, PvA_NRPD, PvA_NRPE gene on G19833 chromosomes was determined by tBLASTn searching against the G19833 genome. Molecular weights (Mol. Wt. ) and isoelectric points (pI) were determined using the Pepstats program from EMBOSS  [45]  analysis package. The number of isoforms in G19833 (v1. 0) and BAT93 (v10) were obtained from corresponding official annotations in the Phytozome (V9. 0) and BAT93 genome data repositories, respectively. Protein similarity and identity percentage were calculated with needleglobal pairwise alignment  [45]. The number of introns in the CDS was obtained from manual reannotation performed in the Artemis platform  [35].
RNA-Seq Data Analysis RNA-seq data from G19833 genotype, were downloaded at https://www. ncbi. nlm. nih. gov/sra?linkname=bioproject_sra_all&from_uid=41439 (accessed on 1 December 2020), for 11 different organs including: roots_10DAP (days after planting), trifoliates_19DAP, young_pods, Leaves_10DAP, stem_10DAP, stem_19DAP, nodules_19DAP, roots_19DAP, mature_pods, flower_buds, flowers  [30]. RNA-seq count data were transformed as moderated log-counts-per-million using the package EdgeR (version 3. 16. 4, [46] ) in the statistical software 'R' (version 3. 3. 2, [47] ). Then for each subset of genes, we used the MixOmics R package (version 6. 1. 1, [48] ) to run a hierarchical clustering on both genes and organs using the Euclidean distance and Ward method.
Common Bean Pol IV and Pol V In order to gain insight into the Pol IV and Pol V complex in the common bean genome, the largest and second-largest subunits of Pol IV and Pol V were searched by seeking AtNRPD1, AtNRPE1, and AtNRPD2/NRPE2 against common bean BAT93 and G19833 genomes with tBLASTn. Common bean encodes one NRPD1, one NRPE1, and one NRPD2/NRPE2, and hence they are named PvA/M_NRPD1, PvA/M_NRPE1, and PvA/M_NRPD2/NRPE2 (Table  1 ). These three proteins present a high level of identity (> 99%) between BAT93 and G19833. They are located on chromosome 2 (PvA_NRPD1), 11 (PvA_NRPE1), and 9 (PvA_NRPD2/NRPE2) (Figure  2 ). 3. 6. In Silico Expression Pattern of AGO, DCL, RDR, DRB, NRPD1, NRPE1, and NRPD2 Candidate Genes In order to analyze the transcript abundance of these 37 genes in different organs of common bean, we performed a comprehensive gene expression in silico analysis using online RNAseq data for genotype G19833.
Location Protein Geno type Gene Nam e Accession Number Genomic Sequence Coordina tes (5′-3′) No. of Isoforms ORF Length (bp) Length (a. a. ) Mol. Wt. (Da) pI No. of Introns Protein Identity 1 Genotype ARGONAUTE G198 33 1 PvA_AGO1 Phvul. 004G142 900 Chr04 42225570-42218739 1 3189 1063 117406. 63 9. 63 20 99. 6% BAT9 3 PvM_AGO1 PHASIBEAM10 F025775 scaffold0 0773 120996-126407 1 3180 1060 117235. 47 9. 63 20 G198 33 BAT9 3 2 PvA_AGO2a PvM_AGO2a Phvul. 002G100 100 PHASIBEAM10 F005923 (i) Chr02 scaffold0 0040 19669530-19665509 416794-413003 1 1 2913 2913 971 971 109754. 56 109798. 66 9. 13 9. 23 2 2 99. 3% G198 33 BAT9 3 3 PvA_AGO2b PvM_AGO2b Phvul. 006G131 700 PHASIBEAM10 F015105 Chr06 scaffold0 0188 24674782-24679768 213085-218085 2 1 2937 3078 979 1026 111161. 89 116318. 64 9. 29 9. 02 3 2 94.
The demersal fish and cephalopod communities of the continental shelves of the Bay of Biscay and the Celtic Sea have been monitored for more than 30 years by the EVHOE series of fisheries surveys. Since 1987, a total of 4247 stations have been sampled in the fall with a GOV bottom trawl in a depth range of 15 to 600m. The main objective of these surveys is to monitor 22 benthic fish stocks and 10 cephalopods but also to provide a description of the distribution of a total of 250 fish and 50 commercial invertebrate taxa. The dataset (https://doi. org/10. 17882/80041) provides abundance and biomass information by station for all observed taxa. Size distributions for a selection of species are also available. These data are part of a larger set of standardized European surveys that provide essential information for monitoring demersal communities in the Northeast Atlantic.
Introduction In North-East Atlantic, monitoring of exploited populations is based on an European network of observation surveys at sea for both pelagic (International Pelagic Surveys, IPS) and benthic  (International Bottom Trawl Surveys, IBTS)  species. This network is included in the European Data Collection Multi Annual Program (Decision (EU) 2016/1701, EU-MAP Commission EU/2016/1251) to support the implementation of the European Common Fisheries Policy (CFP). Even if the data must be combined with caution  (Moriarty et al. 2020 ), these scientific surveys provide consistent and standardized data (common protocols detailed in ICES, 2017) to ICES assessment and science groups. In particular, the data allow stock assessors to analyze spatial and temporal variations in the distribution and relative abundance of fish populations (notably pre-recruits) as well as those of the biological parameters of the exploited species.
These data thus provide fisheries independent abundance indices for commercially valuable species and to collect hydrographical and environmental information. On the basis of scientific surveys carried out in the North Sea, France aimed to develop comparable monitoring in the Bay of Biscay. In this context, a French groundfish survey, named EVHOE ("EValuation Halieutique de l'Ouest Européen", ICES name "FR-EVHOE-Q4") was initiated in 1987, after two exploratory surveys in 1973 and 1976. A research vessel, "RV Thalassa" (construction year 1960, 66. 1 m length, 10. 4 m width, 5 m draught), deployed a standardized bottom trawl (GOV) to sample different strata in terms of bathymetry and latitude. Benthic and demersal fish and cephalopods catches were identified, tried, weighted, measured and some specific species are aged, sexed and their sexual maturity are described.
Data and methods The EVHOE dataset provides information on catch of benthic and demersal fish and cephalopods of the Bay of Biscay and the Celtic Sea from 1987 to 2020. At the beginning of the series of surveys, the observations were exclusively carried out in the Bay of Biscay. From 1997 onwards the observation area has taken its current extension including the entire Celtic Sea. The research vessel (R/V) also changed in 1997. The "old" R/V Thalassa ("Thalassa I"), the first French stern trawler dated of 1960 and used since the beginning of EVHOE survey was replaced by the actual R/V Thalassa ("Thalassa II") since 1996. Thalassa II is 73. 65 m long and 14. 9 m wide stern trawler (gross tonnage of 3022 t). An intercalibration experiment based on paired hauls was conducted in 1996 to estimate conversion coefficients between vessels  (Pelletier, 1998).
Sampling strategy and gear The usual season of observation is in autumn, but two years  (1988 and 1991)  also offered additional spring observations  (Mahé & Poulard, 2005 ) but these data are not included into the published dataset. On the other hand, a few years were missing from the data series for autumn sampling  (1991, 1993, 1996, 2017)  ; the absence of a survey in these years were usually due to technical problems with the R/V. The studied area was limited to the Bay of Biscay, between the latitudes 43°40'N and 48°30'N, from 1987 to 1989. In 1990, the prospected area was  The trawl used for sampling is a GOV 36/47 ("Grande Ouverture Verticale", see description in ICES, 2017). From the standard GOV trawl, the Exocet Kite is replaced by additional buoyancy 66 floats in-stead of 60, and 21 floats of 4 litters compensate for the weight of Marport sensors placed in the middle of the headline.
The gear has an average horizontal opening around 20. 6 m (wingspread range between 17 and 22m) and vertical opening around 4m (range from 3. 5 to 5m). The doors are plane-oval of 1350 kg. Trawl sweeps of different lengths are used depending on the operating depth: sweep of 50 m for depths less than 140 m, sweeps of 100 m for deeper depths. The net is fitted with a 20 mm codend liner. During the trawling, the gear parameters were monitored by "Scanmar" system (Table  2 ) and in recent years by "Marport" system. The parameters that are monitored are the door spread, the wing spread, the headline height and the height of ground rope. They allow appreciating the behavior of the gear during fishing operations but also to assess the area or even the volume sampled. The accuracy of trawling parameters has therefore evolved over time and the data from the trawl geometry sensors were not recorded until year 2017.
In order to preserve the homogeneity of the dataset, and despite the existence of actual trawl parameters values recorded from 2017 onward, standard median value of horizontal trawl opening (20. 6 m) is utilized. The swept area (about 0. 076 km 2 for a standard 30' tow) was then calculated from the distance covered by the trawl. The file also provides the duration of the haul, which is a useful standard effort value when combining data from different surveys using a similar fishing gear. Moreover, the trawl is equipped with a CTD probe allowing for each station to record temperature, depth and salinity profiles (the latter only for stations less than 300m deep). Additionally, a number of navigational parameters or meteorological variables were also monitored but are not included into the published dataset.
g. some rarely sampled points into enclosed bays). In the central-eastern part of the Celtic sea, we added 4 additional to complete strata coverage. Sampling was carried out with straight tows during the daylight, lasting 30 minutes at the bottom (a minimum of 20 minutes accepted in the protocols to validate a haul) at a constant speed of 4 knots. Some tows were stopped before the end of the total trawl time when excessively high tensions were detected (a sign of large catches) or more recently (from 2018 onward) when a strong pelagic acoustic signal was observed from the on-board sounders. These tows were considered valid and included in the dataset when they lasted at least 20 minutes and that the fishing gear has not suffered any damage. They represent less than 10% of the tows (about 2 to 14 tows per year) with higher proportions in recent years due to the improved control of the trawl variables described above.
However, these data required significant revision and were not included in the submitted version of the dataset. They will be the subject of an additional publication. Data entry on board was initially carried out on paper forms that were then copied to computer databases. Starting in 1997, on the R/V Thalassa 2, a computer system for recording catches ("pupitri") allowed for the automated banking of species and their total weight, with individuals informations (sex, counts, size measurements, maturity) still being entered on paper forms. These data were then transferred to an internal database under "Microsoft Access" software (database specific to the EVHOE campaign, not standardized with others IFREMER databases). From 2014 onwards, data was recorded on board with an open-source software especially developed for fisheries surveys ("Allegro Campagne" software, http://www.
ifremer. fr/allegro/, https://forge. codelutin. com/projects/tutti). From 2016 onwards, the lengths were also measured using an electronic ichthyometer directly connected to the data management system. Only the sizes of the largest individuals (> 85cm) and the weight data of the sub-samples and individuals fish were still entered manually. In addition, a set of automated data control and correction tools were put in place in recent years (both within the "Allegro" software and from separate dedicated tools greatly improved in 2020). These tools have been applied a posteriori on the whole data series; the EVHOE dataset proposed here  (Laffargue et al. 2021 ) has therefore been significantly corrected. The dataset consists of 3 tables in a ". csv" file format (Table  4 ): the "Haul" table provides stations metadata, the "Catch" table including taxa number and biomass, the "Size" table providing length and sex observations for a short list of species.
The data provided are identical to the raw data stored in IFREMER's internal database ("Harmonie") and have not been subject to any modifications other than those necessary to recalculate the total catch in the event of subsampling. The "World Register of Marine Species" (WoRMS Editorial Board, 2020) was used to update the taxonomy (valid names and Aphia ID) by utilizing dedicated R packages (« worms 0. 2. 2" and "worrms 0. 4. 0"). The provision of this dataset makes it possible to give it an official reference (https://doi. org/10. 17882/80041), to make updates more easily accessible and, above all, to provide additional information that is not included in the ICES databases, particularly in connection with the evolution of the protocols. The proposed format will make it possible to link the data coming from other biological compartments (e.
g. benthos) or environmental observations observed on the same survey but not included in the original protocols. A set of videos made on board provide additional elements of understanding of all the operations performed and the protocols applied  (Lesbats et al. 2019a,b). 250 "fishes" (including 34 elasmobranchs, Fig. 3C ) and 50 "commercial" invertebrates species (mainly cephalopods and some crustaceans, gastropods and bivalvia, Fig. 3B-D ) but does not include the 408 taxa of others non-commercial invertebrates ("benthos") recently inventoried (from 2008 onwards). In the complete dataset for both the Bay of Biscay and the Celtic Sea, pelagic fish largely dominate the catches both in number and biomass (Fig. 4 ) with 6 main species (Capros aper, Trachurus trachurus, Micromesistius poutassou, Scomber scombrus, Engraulis encrasicolus and Sardina pilchardus) and this even if the trawl used does not target and presents a very relative efficiency for this compartment.
Among the demersal fish for the whole series of data, 3 species (Merluccius merluccius, Trisopterus minutus, Trisopterus luscus) largely dominated the catches in the Bay of Biscay, in the Celtic Sea the pout (T. minutus) is also among the main species but this area stands out with the dominance of Trisopterus esmarkii, haddock (Melanogrammus aeglefinus) and whiting (Merlangius merlangus). However, the complete biological dataset, particularly for the Bay of  Biscay (1987-present) , should be considered with caution. The change of vessel in 1996 and the intercalibration work has shown significant differences in the catchability of the gears for some of the species caught. A number of conversion parameters between the 2 research vessels were proposed  (Pelletier, 1998)  but they do not cover all the species observed.
Moreover, some species are poorly captured by the gear used (e. g. burrowing crustaceans like Nephrops, or flatfishes like Solea solea) or the sampling strategy does not correctly reflect their distribution for part or all of their life history (e. g. species with juvenile in shallow water nurseries). The low sampling effort in the shallowest areas (strata 1) in comparison with the diversity of habitats and associated communities makes the description of benthic communities by this dataset unreliable in this strata. Observed total species richness varies among year and main areas with three main periods (Fig. 5A-B  ). The similarity of the species list within these years groups is also stronger (see cluster results for the years, Fig. 5C-D ). Although at the survey level an evolution of the sampling strategy may account for differences in diversity (e.