dataesr/scientific-paragraphs-categorization huggingface dataset:
Medicanes The dynamics of known medicane cases are discussed in detail in Sect. 4. 2. Regarding their climatology, several studies focused on tracking medicanes in multi-year datasets. However, the lack of a physical definition of medicanes produced different climatologies. The criteria used varied from subjective identification of tropical-like characteristics  (Tous et al. , 2013)  to the application of cyclone phase-space analysis  (Hart, 2003)  and wind thresholds in high-resolution simulations (e. g. Cavicchia et al. , 2014a). Recent studies used dynamical downscaling of ERA-Interim reanalysis  (Gaertner et al. , 2018; Ragone et al. , 2018)  and ERA5 reanalysis  (Zhang et al. , 2020; de la Vara et al. , 2021)  to identify medicanes in a climatological framework. Results showed rather large differences in their climatologies even among the same model simulations but using different parameterisations.
g. Cavicchia et al. , 2014a; Picornell et al. , 2014; Gaertner et al. , 2018; Zhang et al. , 2020). However, such studies used different methods and datasets, failing to reach consensus on the physical definition of medicanes. In contrast to typical tropical cyclogenesis, results from several case studies regard medicanes as baroclinic cyclones that evolve in the mature stage into vortices with structural characteristics similar to tropical cyclones, i. e. an axisymmetric, deep warm core, generally with a windless centre surrounded by strong winds. This is a consequence of the different environmental conditions in which medicanes and tropical cyclones de-velop. The first difference is the wind shear, which is weak near the tropics, while it systematically affects the Mediterranean region due to the southern deviations of the polar jet and the possible presence of the subtropical jet.
Use of observations and data assimilation Having insufficient routine observations for data assimilation requires the adoption of strategies that account for regional specificities, such as severe coastal impact of intense convective systems initiated over the sea within cyclones and interactions between the airflow and the mountains. A systematic investigation of the forecast challenges related to Mediterranean cyclones was performed during MEDEX through the production of one of the first databases of Mediterranean cyclone tracks  (Campins et al. , 2011; Picornell et al. , 2011). In this framework, high-impact weather prediction in the Mediterranean was improved as a direct result of advancements in understanding the most important (thermo-)dynamical processes in Mediterranean cyclones and of the onset of observational targeting strategies  (Jansa et al.
Heavy precipitation and relevant impacts The important role of cyclones in provoking the majority of heavy rainfall was established by  Jansa et al. (2001)  in the context of MEDEX. The authors used observations and cyclone databases to show that 90 % of heavy rainfall events in the western Mediterranean were indeed associated with cyclones of diverse intensity. More recently,  Flaounas et al. (2018)  showed that weak and intense Mediterranean cyclones are both capable of producing high precipitation amounts. On the other hand, when considering rainfall averages and cyclone intensities, a linear relationship was found between rainfall and cyclone intensity. Regardless of their intensity, cyclones have been shown to play a dominant role in regional precipitation with contributions exceeding 70 % of the annual total  (Hawcroft et al.
, 2012; Pfahl and Wernli, 2012). Concerning extremes,  Pfahl et al. (2014)  and  Flaounas et al. (2016)  analysed climatological datasets from reanalysis and regional climate models to show that, depending on the region, intense cyclones may contribute 60 % and up to more than 90 % of regional extreme rainfall. The processes that produce heavy precipitation and relevant extremes might differ from case to case. In a global analysis  Pfahl et al. (2014)  showed that about 40 % to 50 % of the regional extremes can be attributed solely to WCBs in the Mediterranean (feature 5 in Fig. 3 ), while  Flaounas et al. (2018)  showed that WCBs typically produce more than twice the precipitation amounts related to deep convection (features 6, 7 and 8 in Fig. 3 ). These two different processes of precipitation production were analysed in two contrasting case studies that took place during the SOP1 campaign of HyMeX in October 2012 and were both located in the West Mediterranean, close to the Alps  (Flaounas et al.
In the framework of MEDEX, societal impact research has focused on flood events, populating the first database of its kind for the region. This database has been the basis for other relevant works in the framework of HyMeX, which resulted in the FLOODHYMEX database  (Llasat et al. , 2013; Papagiannaki et al. , 2013). This effort has been recently updated and extended to the Mediterranean Flood Fatalities (MEFF) database spanning from 1980 to 2015  (Petrucci et al. , 2019). Vinet et al. (2019)  and  Petrucci et al. (2019) , based on the MEFF database and its extended version EUFF (European Flood Fatalities) covering the period 1980-2018, have shown that the flood-related mortality mainly occurs during early autumn in the western Mediterranean and during late autumn and winter in the eastern Mediterranean.
A few studies have analysed the impact of the sea state to ship accidents in the region. In particular,  Bertotti and Cavaleri (2008)  and  Cavaleri et al. (2012)  analyse two case studies in which sea waves under the influence of intense Mediterranean cyclones were responsible for two ship accidents in February 2005 and March 2010, respectively. In both cases, waves of more than 10 m were reported to hit the vessels and cause substantial damage and loss of human life. More recently, Zhang and Li (2017) used the International Maritime Organization (IMO) database for ship accidents in the period 2001-2010 and showed that the Mediterranean Sea is one of the main regions in the globe with more frequent ship accidents induced by sea waves. Despite the direct relationship of cyclones to wind speed extremes in the region, a more thorough study is needed to better determine whether cyclones have indeed led to these accidents.
Extending the scope of climatological studies for Mediterranean cyclones The analysis of Mediterranean cyclone tracks in a climatological context has been one of the most investigated topics. Despite the different approaches, reanalysis datasets and cyclone tracking methods, recent studies present high agreement on the tracks density, seasonal cycle and favourite locations of cyclogenesis. Several subtypes of cyclones have also been identified, and a high number of studies have addressed their climatological aspects. Nevertheless, open questions still remain on the future evolution of Mediterranean cyclogenesis and associated impacts. In these regards, the special case of medicanes has drawn most of the attention using a plethora of different criteria for their detection. However, the rarity of medicanes and the lack of agreement in their physical definition prohibits a solid interpretation of the results.
Acknowledgements. The authors are thankful to three anonymous reviewers and  Tim Woollings  for their encouraging reviews, the constructive comments and all suggestions that greatly improved the manuscript. This article is based upon work from  COST Action CA19109  "MedCyclones", supported by  COST -European Cooperation in Science and Technology  (http://www. cost. eu,last access:  28 January 2022 ). Financial support. Silvio Davolio  and  Mario Marcello Miglietta  were supported by the project " Climate change: risk mitigation for sustainable development " funded by the  Italian Ministry for Education, University and Research (MIUR). Miguel Angel Gaertner  has been supported by the  Spanish Ministry of Science, Innovation and Universities , the  Spanish State Research Agency , and the  European Regional Development Fund  through grant  CGL2017-89583-R (IBERTROPIC project ).
Samira Khodayar is supported by the  Talented Researchers Support Programme -Pla GenT -CIDEGENT  by the  Ministry of Innovation, Universities, Science and Digital Society, Generalitat Valenciana (GVA) , project  MED-EXTREME  ( CIDEGENT/2018/017 ). Marco Reale  has been supported in this work by  OGS  and CINECA under HPC-TRES award number  2015-07  and by the project  FAIRSEA (Fisheries in the Adriatic Region -a Shared Ecosystem Approach ) funded by the 2014-2020  Interreg V-A Italy-Croatia CBC Programme  (standard project  ID 10046951 ). Victor Homar has been supported by the  Spanish Ministry of Science, Innovation and Universities , the  Spanish State Research Agency , and the  European Regional Development Fund  through grant  CGL2017-82868-R (COASTEPS ). Shira Raveh-Rubin  has been supported by the  De Botton Center for Marine Science.
, 2006) , with Eurasian rivers showing the greatest increase. Box et al. (2019)  assessed the temporal trends in discharge for six of the largest Eurasian rivers (the Ob, Pechora, Severnaya Dvina, Yenisey, Lena, and Kolyma rivers) and for the two major North American Arctic rivers (the Mackenzie and Yukon rivers). For the composite Eurasian river dataset, river flows increased on average by 18. 7 km 3 per decade between 1981 and 2011, whereas the two North American rivers exhibited an increase of 5. 9 km 3 per decade between 1975 and 2015. These volumetric increases correspond to a 12% increase for Eurasian rivers and a 9% increase for North American rivers over approximately the past three decades.
Acknowledgements This review is a result of efforts led by the  Arctic Monitoring and Assessment Programme (AMAP)  and the  AMAP Mercury Expert Group  to produce the 2021 AMAP Mercury Assessment. We thank assessment leads  Rune Dietz  ( Aarhus University ) and  Simon Wilson (AMAP)  for their guidance, support, and technical insights on the material. Graphics production and technical editing were supported by  AMAP. Institutional support for this review was provided by  Environment and Climate Change Canada. Henrik Skov acknowledges The  Danish Environmental Protection Agency  ( DANCEA funds for Environmental Support  to the  Arctic Region  project; grant no. 2019-7975 ) and the  European ERA-PLANET  projects; iGOSP and iCUPE (consortium agreement no. 689443  for both projects) for financial support.
Materials and Methods Our methodology is similar to the one used by  Ragoasha et al. (2019) : the inter-annual variability of transport success was investigated from 1992 to 2011 using Lagrangian experiments ran using an off-line tracking algorithm called Pyticles  (Gula et al. , 2014)  fed with 20 years of daily three-dimensional velocity fields derived from an inter-annual numerical simulation of the oceanic circulation. However, the model simulation is now based Adapted from  Nelson (1989). *The South African Sardine and Anchovy Recruitment Program (SARP) line is an across-shore section off Cape Point (34°S) used to assess the transport success of sardine and anchovy eggs and larvae  (Fowler & Boyd, 1998; Hampton, 1996). 10. 1029/2020JC017114 4 of 25 on a higher resolution 3-km nested grid that allows for the first time the impacts of fine-scale dynamics of the Benguela Upwelling System to be investigated.
The 3-km Model Simulation This new simulation was run with an off-line and one-way nested approach consisting of a 3-km child grid embedded in a 7-km parent grid (Figure  2 ). The lower resolution parent simulation (R7KM) supplies boundary conditions to the higher resolution child simulation (R3KM). Boundary conditions are prepared using the roms-2roms algorithm  (Mason et al. , 2010). The parent simulation is fully described in  Ragoasha et al. (2019). The bottom topography for the child grids was also extracted from the Shuttle Radar Topography Mission (SRTM 30 plus) data set (available at http://topex. ucsd. edu/www. html/srtm30. plus. html), subsequently interpolated on the higher resolution grid, and then smoothed similarly to the parent simulation. The same 6-hourly atmospheric forcing (heat, fresh, and momentum fluxes) provided by the CFSR atmospheric reanalysis at 0.
Discussion and Conclusions In the southern Benguela upwelling system (SBUS), variability in the annual recruitment of small pelagic fish has long been a significant concern to fisheries oceanographers. To be transported to a suitable nursery area is one of the factors required for the survival of fish larvae, and this study was aimed at relating anomalous transport success events to local physical processes such as (a) wind surface forcing (Ekman transport, Benguela Jet, poleward current) and (b) mesoscale dynamics. The inter-annual variability in physical transport processes was investigated using a 3-km high-resolution simulation forced with 6-hourly atmospheric CFSR data provided for 20 years  (1992) (1993) (1994) (1995) (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) (2006) (2007) (2008) (2009) (2010) (2011).
Acknowledgments The authors acknowledge the funding of  N. Ragoasha 's PhD by the  South-African National Research Foundation  ( NRF, South Africa ) and the  French Institute for Research and Sustainable Development (IRD, France). This study was also supported by the  French national program LEFE/INSU  under the project' s name Benguela Upwelling Innershelf Circulation (BUIC ). This study was granted access to the HPC resources of [ TGCC/ CINES/IDRIS ] under the allocation 2017-[ DARI no. A0020107443  ] attributed by  GENCI  ( Grand Equipement National de Calcul Intensif ).
Genetic analysis A total of 132 sloughed skin samples were collected between 2017 and 2020 (Table  S2 ). They were assigned in the field to 41 different sperm whales, i. e. to 18 adult females and 10 immatures (Table  S2  and  Sarano F. et al. 2021 ) and to 13 adult males (Table  S2 ). Mitochondrial and nuclear loci were amplified, allowing an analysis of variation over 638 bp of the MCR (Genbank references: MK907146-MK907148, MK907159, MK907163, MK907172, MW854724-MW854731 and MW929445-MW929452) and at 16 polymorphic microsatellite loci (Table  S1 ). The Identity Analysis based on microsatellite polymorphisms performed in CERVUS identified thirteen genetically distinct individuals from Mauritius corresponding to the 13 adult males identified in the field (all pID <2. 45e -12 ). All genotypes assigned to the same individual had between 87.
It also overlapped fully with the 283bp fragment and partially with the 563bp fragment (514bp in common) determined by  [45]. A new dataset that included all these sequences was constructed to allow a large-scale comparison between mitochondrial haplotypes. The numbers of (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. haplotypes, the haplotype diversity (H) and the nucleotide diversity (π) were calculated using the program DnaSP, V. 5. 10. 01  [61]. The software Arlequin, V3. 5. 1. 2 [62] , was used to calculate FST and ΦST, fixation index estimators for mitochondrial genomes. Fragment sizes were determined using the "Microsatellite Plugin" of Geneious Pro v. 7. 1 (Biomatters Ltd, Auckland, New Zealand). All the molecular analyses were performed in at least two independent experiments, from different samples of a same individual when available, or twice from the same sample following Sarano et al.
Kinship analysis Kinship analyses were performed on the complete dataset (with duplicate samples removed), that is adult females and immatures previously analysed  [21]  with the newly sampled Chesna (sampled in 2020, Table  S2 ), and all the males sampled in Mauritian waters (n=13) and in Crozet/Kerguelen (n=8). Kinship analysis followed the same methodology as described in  [21]. Briefly, we first used different estimators to calculate the relatedness coefficient r between all the genotyped individuals using the R package Related  [64]  and the software ML relate  [65]. Related was used to determine that the r estimators W  [66]  and L&L  [67]  had the highest correlation between observed and expected relatedness values and were thus selected to calculate the relatedness coefficients. ML relate  [65]  was used to calculate a relatedness coefficient based on the probabilities of sharing alleles identical by descent, and to assign the most probable familial relationships (among parent-offspring (PO), full sibling (FS), half-sibling (HS), unrelated (U)) to each dyad.
Acknowledgements We thank  Navin Boodhonee  and the  Blue Water Diving Center (Trou aux Biches, Mauritius)  for their all years round field work. A special thanks to  Carole Decker  ( Brest, France ) for her help with the lab experiments, and to  Marine Pensec  and  Cédric Le Maréchal  ( Laboratoire de génétique moléculaire et d'histocompatibilité, CHRU, Brest France ) for their help with microsatellite analysis. We are very grateful to  Marion Sarano  (https://marionsarano. fr/graphiste-freelance/)who made the drawing of the figure 2.
Availability of data and materials (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint this version posted July 15, 2021. ; https://doi. org/10. 1101/2021. 04. 23. 440733 doi: bioRxiv preprint P. 23 / 28 The datasets supporting the conclusions of this article are included within the article and its additional files. Mitochondrial DNA sequences have been deposited into the Genbank, references MK907146-MK907148, MK907159, MK907163, MK907172, MW854724-MW854731 and MW929445-MW929452.
To date, 50 fully assembled OsHV-1 genomes are available in public databases, those genomes have been sequenced and assembled using various protocol and sequencing technologies (Table  S1 , available in the online version of this article). Although recent genomes have been obtained from short-read mNGS  [31] [32] [33] [34] , OsHV-1 complete genome assembly remains a complex process. Indeed, a short-read approach is ideal for the identification of small-scale variation like SNPs but this technology struggles to identify variations at a larger scale like structure variations (SV) or large inverted and repeated regions. Due to its intrinsic.
Illumina genome assembly Illumina raw reads files were quality filtered (PHRED score >31) and adapters trimmed with Fastp version 0. 20. 1  [72]. To evaluate the origin of reads, fastq reads were aligned to the oyster C. gigas genome (accession: GCA_902806645. 1) and to OsHV-1 µVar A genome (accession: KY242785. 1) with Bowtie2 version 2. 4. 1  [73]. All the non-oyster reads were then selected with Samtools version 1. 9  [74]  and Seqtk version 1. 2 (https://github. com/lh3/seqtk). Those reads were then used for de novo assembly with SPAdes version 3. 14. 0 with parameter -meta  [75]. The de novo OsHV-1 contigs generated by SPAdes were then identified with blastn version 2. 6. 0  [76]  using OsHV-1 µVar A sequence as a query (accession number: KY242785. 1). The identified OsHV-1 contigs were then manually scaffolded in Geneious Prime (version 2020.
nanopore genome assembly Nanopore fast5 file were GPU base called with Guppy version 5. 0. 7 with standard parameters except -config dna_ r9. 4. 1_ 450bps_ hac. cfg (https://community. nanoporetech. com/downloads). Fastq reads were then 100 bp trimmed at their beginning and at their end to ensure proper adapter removal with SeqTk version 1. 3 with parameters -b 100 and -e 100 (https://github. com/lh3/seqtk). To assign reads to either host or viral origin, fastq reads were aligned to the oyster C. gigas genome (accession: GCA_902806645. 1) and to OsHV-1 µVar A genome (accession: KY242785. 1) with Minimap2 version 2. 22 with standard parameters  [79]. Then two types of de novo assemblies were performed with non-oyster reads with two different de novo assemblers. All fastq reads or only the top 10 % of the longest reads were used as input for de novo assembly with Flye version 2.
8. 3 and parameters -meta  [80]  or with Canu version 2. 1. 1 and parameters -nanopore  [81]. OsHV-1 de novo assembled contigs were then identified with blastn  [76]  against the OsHV-1 µVar A genome and were manually trimmed in Geneious version 2020. 2. 4 (https://www. geneious. com). All de novo contigs plus the new assembled OsHV-1 genome were then polished using Nanopore reads with three run of Racon version 1. 4. 20 with parameters --no-trimming -m 8x-6 g -8 w 500  [82]  and one run of Medaka version 1. 4. 3 with parameters medaka_consensus (https://github. com/nanoporetech/medaka). For OsHV-1 isoform coverage evaluation, the four contigs produced by Canu with the top 10 % of the longest reads were trimmed on the U L side to keep a 10 kb U L fragment with Geneious version 2020. 2. 4 (https://www.
geneious. com). The four major isomers were then used as a reference for reads mapping with Minimap2 version 2. 22 with standard parameters -axe map-ont (https:// github. com/lh3/minimap2). Samtools version 1. 10  [83]  were then used to filter out all the shortest aligned read and all the alignment with MapQ <40, keeping only the reads spanning at least a fragment of the U L and a fragment of the U S (i. e. 28 kb long). A pipeline summary can be found in Fig. 2b.
non-osHV-1 contigs' classification Polished non-OsHV-1 contigs with a size larger than 10 kb were then subjected to taxonomic identification and classification with phaster  [84]  accessed in September 2021, with blastn version 2. 0. 9 with parameters -max_hsps 1 -max_target_seqs 100 -evalue 0. 0001  [76]  or with diamond blastx  [85]  version 2. 0. 6 with parameters --sensitive --max-hsps 1 --max-target-seqs 0 --range-culling -F 15 --evalue 0. 0001 against the refseq database accessed in September 2021.
osHV-1 phylogeny In order to illustrate the global phylogenetic relationships among our and other available genomes, 13 OsHV-1 NR-genomes (11 available in GenBank: AY509253, GQ153938, KP412538, KY242785, KY271630, MG56175, MF509813, OM811579, OM811584, OM811586, OM811594 and the two from this study) were aligned with progressiveMauve algorithm  [87]  implemented in Geneious version 2020. 2. 4 to local collinear blocks. Reordered genomes block were then aligned with MAFTT version 7. 4 using default parameters  [86]  implemented in NGPhylogeny. fr  [88]. Alignment was cleaned with BMGE with default parameters  [89]  implemented in NGPhylogeny. fr. The best fitting model of nucleotide substitution was chosen according to the Akaike Information Criterion with jModelTest version 2. 1. 10 with default parameter  [90].
Tree was constructed with phyML version 3. 3  [91]  with default parameters except '-b 100 m HKY85 -f m -c 8 s BEST -a e -v e -o tlr' implemented in NGPhylogeny. fr. Phylogenetic tree was midpoint rooted and arranged in FigTree version 1. 4. 4 (https://github. com/rambaut/figtree).
osHV-1 genome assembly using nanopore reads Since this is the first time that an OsHV-1 genome has been assembled from ONT long-read, we decided to evaluate the two most used long-read de novo assembler Flye and Canu with two datasets: (i) all the Nanopore reads and (ii) only the top 10 % longest Nanopore reads (see Methods for further detail) (Fig. 4b ). Whatever the dataset used, Flye yielded the same two contigs; a long one (164 kb) corresponding to the complete U L and a short one (40 kb) made of the U S surrounded by one copy of IR L -X-IR L on its left side and one copy of TR S -X-TR L on its right side (Fig. 4b ). With the dataset including all Nanopore reads, Canu yielded one large OsHV-1 contig (262 kb). This contig is made of one fragment of the U L (32 kb) followed by a fragment made of the U S surrounded by one copy of IR L -X-IR S on its left side and one copy of TR S -X-TR L on its right side (40 kb), followed by the complete U L (164 kb) and followed by another fragment made of U S surrounded by one copy of IR L -X-IR S on the left side and one copy of the TR L (24 kb) on its right side (Fig.