dataesr/scientific-paragraphs-categorization huggingface dataset:
TE copies with a length greater than 10 kb likely represent nested TE copies and were particularly abundant in the young stratum of M. v. paradoxa, called the white stratum (Supplementary Fig. 3A ). Because retrotransposons such as LTRs can be common in plants  74, 75  , we investigated whether horizontal transfers of TEs could have occurred between the host plant and Microbotryum genomes. We compared the sequences from the plant Repbase database to the annotated TE sequences in Microbotryum genomes by blast. We obtained several BLAST hits with high identity and low e-value scores, but none exceeded 6% of the annotated TE sequence lengths (Supplementary Data 3). Therefore, no putative inter-kingdom horizontal TE transfer was identified. DNA transposons were predominantly represented by Helitrons and terminal inverted repeats (TIR) elements in most Microbotryum genomes (1.
Temporal dynamics of TE accumulation in non-recombining regions The multiple independent events of recombination suppression across the Microbotryum phylogeny, with a range of ages, provides a unique opportunity to investigate the temporal dynamics of TE accumulation. The large non-recombining regions of different ages formed by the stepwise recombination suppression between the HD and PR loci were highly rearranged in M. v. viscidula, M. v. melanantha, M. v. gracilicaulis and M. v paradoxa, rendering difficult the assignment of some TE copies to a given age of recombination suppression. In order to be conservative, we only considered TE copies that could be assigned to a stratum with high confidence, by taking into account only blocks of at least 80 kb (size of the pink stratum, the smallest stratum of the dataset) and encompassing at least two genes of a given stratum.
Discussion We found a large degree of variation among Microbotryum species in their overall TE load, and the key to understanding this variation seems to be the evolution of the recombination landscape in regions determining reproductive compatibility. Moreover, there appears to be a significant feedback of TE accumulation on non-recombining matingtype chromosomes where the buildup is rapid, and the rest of the genome is then burdened with greater repetitive element insertions. Leveraging a unique dataset with 21 regions having independently evolved recombination suppression, we found that TEs accumulated rapidly following recombination cessation but then reached a plateau at ca. 50% of occupied base pairs, after 1. 5 MY. We revealed more details on the degree of variation in genomic TE loads among Microbotryum genomes than previously recognized, ranging from 6.
In conclusion, this study leverages a unique dataset of 21 independent evolutionary strata of different ages in closely related species to assess the dynamics of TE accumulation with time following recombination suppression. We show that TEs have rapidly accumulated following recombination cessation and that the TE accumulation slowed down abruptly after 1. 5 MY. We further show that some superfamilies repeatedly expanded in independent non-recombining regions, and in particular Helitrons that were not yet abundant before recombination suppression. Copia and Ty3 superfamilies were also over-represented in non-recombining regions and have accumulated through bursts of proliferation, both in the non-recombining regions of the mating-type chromosomes and in the autosomes of Microbotryum species at the same time; this finding is in agreement with the TE reservoir hypothesis, although direct evidence is lacking.
Detection and annotation of TEs Transposable elements (TEs) were detected de novo in the a 1 and a 2 haploid genomes of 16 Microbotryum species, two strains of M. lychnidis-dioicae (1064 and 1318), and the red yeast Rhodothorula babjavae using LTRharvest 90 from GenomeTools 1. 5. 10, performing long-terminal repeat (LTR) retrotransposons detection and Repeat-Modeler 1. 0. 11  91  combining results from three other programs: RECON  92  , RepeatScout  93  and Tandem Repeats Finder  94. The TE detection was enriched by BLASTn 2. 6. 0+  95  using the genomes as a database and the previously detected TE models as queries. To fulfill the repeat criterion, a TE sequence detected by RepeatModeler or LTRHarvest and its BLAST hits were retained only if the query matched at least three sequences in the same species with an identity ≥ 0.
8, a sequence length > 100 bp and a coverage ≥ 0. 8 (defined as the query alignment length with removed gaps divided by the query length). When these criteria were met, we retained the other query matches for the following parameters: identity ≥ 0. 8, sequence length > 100 bp, evalue ≤ 5. 3e -33 (25th percentile of e-value distribution) and coverage ≥ 0. 8. We performed TE annotation 2 using the fungal Repbase database 23. 05  96  based on sequence similarity. We first performed a BLASTn search and a BLASTx search using the fungal Repbase DNA and protein sequence database, respectively, with TE sequences as queries. For each of these similarity-based searches, we set the minimum e-value score at 1e -10 and minimum identity at 0. 8. Then, we performed protein domain detection using pfam_scan.
pl (ftp://ftp. ebi. ac. uk/pub/ databases/Pfam/Tools/) on TE sequences and compared them to protein domain detection in the fungal Repbase database, keeping matches with e-values ≤ 1e -5. We also considered the annotation found by RepeatModeler. In order to determine the best annotation of a TE sequence, we applied a majority rule: we chose the most frequent annotation, and, in case of equality, we kept both annotations, generating a multiple annotation; these multiple annotations can be due to TEs being inserted within other TE copies, generating nested TEs. When we found no annotation, we assigned the TE sequence to an "unclassified" category; we discarded such annotations when overlapping with predicted genes to avoid false positives. We also discarded predicted TE sequences annotated as rRNA or overlapping Microbotryum ribosomal sequences (downloaded from https://www.
Search for potential TE horizontal transfers To search for potential horizontal transfers of transposable elements between Microbotryum fungi and their host plants, we compared the nucleotide sequences from the Repbase database 23. 05  96  of Dicotyledones and Arabidopsis thaliana with the Copia and Ty3 TE annotations from the Microbotryum genomes using BLASTN 2. 6. 0+  95.
RIP-like index We computed values for a RIP-like index in non-overlapping 1 kb genomic regions along the mating-type chromosomes and autosomal contigs as previously described 114. The RIP-like index was calculated as the ratio t/n, t being the ratio of the RIP-affected sites (TTG + CAA trinucleotides, forward and reverse  62  ) over the non RIP-affected sites (TCG + CGA, minus overlapping tetra-nucleotides TGCA) for the RIP target sites, and n being the same ratio for non-RIP target sites ( [A,C,G] TG + CA[C,G,T] over [A,C,G]CG + CG[C,G,T] -[A,C,G]CG[C,G,T] ), to control for sequence composition. The RIP index was normalized as t/n -1, so that a normalized RIP index greater than 0 was indicative of an excess of RIP-like mutations compared to random expectations. The script used to compute the RIP index is available at https://gitlab.
com/ marine. c. duhamel/ripmic. We used the SlidingWindow function of the evobiR 1. 1 package (mean values, 10 kb steps 115 ) and ggplot2 3. 4. 0 116 to plot the distribution of RIP along the mating-type chromosomes and autosomal contigs and identify the RIP-affected regions. We used the same parameters to plot the density of genes and TEs in the same nonoverlapping 1 kb windows. In order to test the relationship between the abundance of RIP footprint in TEs in non-recombining regions and the age of evolutionary strata, we calculated the average of the RIP index of the TEs in each stratum and performed a two-sided Pearson's correlation test.
In M. v. viscidula, M. v. melanantha, M. v. gracilicaulis and M. v paradoxa, recombination suppression extended gradually to link the HD and PR loci and then underwent multiple rearrangements that intermingled their genes and TEs. In order to avoid misassignment of TEs to these intermingled strata, we only considered regions spanning at least 80 kb (corresponding to the size of the smallest stratum from the dataset, the pink stratum in M. v. paradoxa) and with only genes from a single stratum. We defined the limit between two strata as the middle point between two genes from two distinct rearranged strata. The resulting blocks assigned to strata overall represented 66. 52% to 90. 26% of the total non-recombining regions formed by intermingled strata (Supplementary Fig. 18 ), which should thus give a good estimate of the stratum TE contents.
intermedium, i. e. , the Microbotryum species most distant from the other species in our dataset, with unlinked mating-type loci and with little recombination suppression  66. To test whether TEs also preferentially accumulate at the margin of the non-recombining regions, we compared for each species the fraction of base pairs occupied by TEs within the 100 kb of the pseudoautosomal regions flanking the non-recombining regions to the distribution of TE load in 100 kb non-overlapping windows in fully recombining autosomes (100 kb away from the centromeres and after removal of 20 kb corresponding to subtelomeric regions). We only considered the species with a length of the pseudo-autosomal region at least equal to 100 kb (thus excluding M. v. paradoxa) and with at least 30 non-overlapping windows of 100 kb on their autosomes (thus excluding M.
Estimates of non-recombining region ages In Microbotryum fungi, sexual reproduction occurs before the infection of a new plant, which will produce spores in its flowers at the next flowering seasons, so that one year corresponds to one generation for these fungi. We used the dates of recombination suppression estimated in previous studies  37, 66  , for 21 genomic regions corresponding to independent events of recombination suppression distributed across 15 Microbotryum species. The M. scabiosae non-recombining regions used in a previous study  37  was not considered here due to the large confidence interval on its estimated age. To this dataset of 15 Microbotryum species, we added the TE content in the autosomes of M. intermedium as the zero time point; indeed, the autosomes are recombining and there is little potential for a reservoir effect in M.
d S plot calculation We calculated the synonymous divergence (d S ) from the alignment of a 1 and a 2 allele sequences using MUSCLE  99  implemented in TranslatorX v1. 1 100. We computed the d S and its standard error using the yn00 v4. 9 f program of the PAML package 119 and plotted them using the ggplot2 2 3. 4. 0 116 in R. Standard errors were calculated per gene by PAML using the curvature method, i. e. , by inverting the matrix of second derivatives of the log-likelihood.
In order to test whether a phylogenetic signal could bias the analysis of the dynamics of TE accumulation with time, we performed a regression of TE content against stratum age using the pgls function of the caper package version 1. 0. 1 122 and an ultrametric tree of the evolutionary strata. We constructed the ultrametric tree based on the species tree topology 66 to which we added the splits corresponding to the following evolutionary strata: the black stratum shared by M. v. caroliniana and M. v. parryi, the two independent purple-to-centromere strata in M. lagerheimii and in M. saponariae, the brown, light-brown, black and pink strata in M. v. paradoxa, the light-gray stratum shared by M. v. gracilicaulis, M. v. melanantha and M. v. viscidula, and the dark-grey stratum shared by M. v. melanantha and M.
Acknowledgements We thank  Dominik Begerow ,  Sebastian Klenner ,  Lena Steins , and  Frederick Witfeld  for providing useful comments on the manuscript. We thank  Gilles Fisher ,  Paul Jay ,  Jacqui Shykoff , and  Olivier Gascuel  for useful discussions. This work was supported by the  National Institute of Health (NIH)  grant  R15GM119092  to M. E. H. , the  Louis D. Foundation  award and the  EvolSexChrom ERC  advanced grant # 832352  to T. G. and a public PhD grant to M. D. overseen by the  French National research Agency (ANR)  as a part of the " Investissements d'Avenir" through the program  " Action Doctorale Internationale ,  ADI 2018 " project funded by the  IDEX Paris-Saclay  ( ANR-11-IDEX-0003-02 ).
Data availability All data generated or analyzed during this study are included in this published article and the supplementary information files (Supplementary Tables  1 2 3 4 and Supplementary Data 1-6). Datasets in figshare are described in Supplementary Note 1. The rRNA or overlapping Microbotryum ribosomal sequences were downloaded from https:// www. arb-silva. de/ and http://combio. pl/rrna/taxId/5272/ and mitochondrial DNA sequences from GenBank (NC_020353). TE sequence similarity searches were performed using Repbase database 23. 05. Sequencing data and genome assemblies were published previously and available at GenBank under the BioProjects PRJEB12080, PRJNA437556, PRJEB16741, PRJEB15277, PRJNA771266 and PRJNA437556. All fungal strains are available upon request. Source data are provided with this paper.
Community data collection We collected data from the North Sea International Bottom Trawl Survey (NS-IBTS) from the publicly available scientific monitoring survey DATRAS, hosted by the International Council for the Exploration of the Sea (ICES) (https://datras. ices. dk). The temporal span of the data was restricted to winter and summer surveys (i. e. first and third quarters of the calendar year) for the period between 1986 and 2016, for which there is a good coverage of the entire study area. Spatially, the survey is structured on the basis of the ICES statistical rectangles; these are rectangles of 30ʹ in latitude by 1° in longitude (approximately 56 by 64 km at the center of the study area) that divide the area between 36°N and 85°30ʹN and 44°W and 68°30ʹE into grid cells (Fig. 1 ). The ICES statistical rectangles gridding system is a formal spatial structure used in fisheries assessment and marine management advice within ICES.
The DATRAS survey identifies catches at species level whenever possible, which we verified and updated with the World Register of Marine Species (WoRMS Editorial Board 2022) whenever needed. Non-fish taxa were discarded and only organisms identified to species level from the following classes were kept: Actinopterygii, Elasmobranchii, Holocephali, Myxini and Petromyzonti. The data went through a quality check procedure where we removed invalid hauls and invalid species records, which resulted in presence-absence data for 247 species. Since abundances of pelagic species are generally underestimated, due to their lower catchability in bottomtowed gear  (Walker et al. 2017) , we used presence-absence data only, allowing us to represent the entire fish community, including both pelagic and demersal species.
Species traits and phylogeny We wanted to capture the diversity of traits in the community and quantify their role in determining species niches and responses to the environment. We therefore talk about community cluster traits, i. e. traits that translate taxonomic biodiversity into trait diversity  (Streit and Bellwood 2022). We selected eleven traits in order to represent species' morphology, life history, reproduction and diet  (Dencker et al. 2017, Supporting information). Trait values for each species were collected from available trait data bases  (Beukhof et al. 2019a) , supplemented with information from recent literature  Coulon et al. (unpubl. ). Morphology of the species was described as body shape, caudal fin shape and maximum length (cm). Life history was characterized by the age of maturity (years) and the von Bertalanffy growth coefficient K (year -1 ), while reproduction was represented by spawning type, fecundity (number of eggs) and offspring size (egg diameter in mm).
Model fitting and diagnostics To examine the underlying community assembly rules acting on the North Sea fish community we used the HMSC framework  (Ovaskainen et al. 2017 , Tikhonov et al. 2020)  through the R package  'Hmsc' ver. 3. 0-11 (www. r-project. org, Ovaskainen and Abrego 2020, Tikhonov et al. 2021). Similar to other modelling tools, HMSC quantifies the explained variation within the observed communities through included environmental covariates, as well as through random effects, which can account for e. g. patterns arising from spatiotemporal processes. However, HMSC may include random factors that can be linked to species-specific co-occurrence patterns within the unexplained (residual) variation. These random effects are shown through either positive or negative pair-wise species associations reflecting ecological processes that take place in addition to species' responses to the environment (e.
HMSC models species environmental niches by incorporating information on how species traits respond to environmental covariates, denoted as gamma parameters in the model. This allows quantifying how much of the variation in species responses to the environment can be attributed to species traits. Since, traits were found to explain a substantial proportion of species response to surface chlorophyll a, we explored the trait relationship with this variable. We used community-weighted means traits to study such relationships, which can be computed with the 'Hmsc' package  (Ovaskainen and Abrego 2020, Tikhonov et al. 2021). Since many traits are phylogenetically conserved (following niche conservationism, i. e. the tendency of species to retain ancestral traits)  (Wiens and Graham 2005) , we included the phylogenetic correlation parameter rho in our model that measures if the residual variation (after accounting for traits) of species responses to the environment is independent or phylogenetically structured.
Acknowledgements -We would like to thank all contributors of the  North Sea International Bottom Trawl Survey  for their efforts in collecting the fish survey data. We thank two anonymous reviewers for their constructive comments contributing to improve the quality and clarity of the study. Funding -MM acknowledge financial support from the  European Union 's  Horizon 2020 projects  " ECOTIP " (ID:  869383 ). BW acknowledge financial support from the  Strategic Research Council of the Academy of Finland  (grant no. 312650  to the  BlueAdapt Consortium ). ML acknowledges financial support from the  European Union 's  Horizon 2020 project  " FutureMARES " (ID:  869300 ) and from the  European Union 's  Horizon Europe research and innovation programme project  " B-USEFUL " (ID:  101059823 ).
Each of these steps is progressive, building upon the prior changes. Under the "Simulated-Venus" conditions, we also perform tests to find the effusion rate that would reproduce a 100 km long Venusian lava flow. To limit the number of model variables assessed, two assumptions are also made. (a) All initial cases use an effective effusion rate of 700 m 3 /s, which is the value determined by  Ramsey et al. (2019)  to reproduce the Cone II lava flow length. (b) All model runs are conducted over a constant 1° slope, which removes the impact of slope-change on the results and is consistent with larger-scale topography observed across Venus  (Byrnes & Crown, 2002; Flynn et al. , 2021; Mouginis-Mark, 2016; Roberts et al. , 1992). All modeling is conducted using the PyFLOWGO model (https://github.
Conclusion We adapted the terrestrial PyFLOWGO model to Venusian environmental and planetary conditions to assess how each change affects the dynamics of a channelized lava flow emplacement. PyFLOWGO is the preferred model of choice because it accounts for rheologic and thermal changes, is highly adaptable with different modules available, and is easily modified for other planetary conditions. Our modeling was accomplished in five steps by changing the following conditions: (a) gravity (i. e. , "Small-Earth"), (b) ambient atmospheric temperature (i. e. , "Hot-Small-Earth"), (c) atmospheric specific heat capacity and wind speed (i. e. , "Venus-light"), (d) atmospheric density (i. e. , "Venus-Heavy"), (e) and coupling atmospheric convective and radiative heat flux (i. e. , "Simulated-Venus").
, 1993; Lancaster et al. , 1995). FLYNN ET AL. With the three planned missions to Venus (i. e. , DAVINCI+, VERITAS, and EnVision) in the next decade, new surface emissivity data, improved atmospheric knowledge, higher resolution radar surface images, and topography will become available. Specifically, one of the key science objectives of the VERITAS mission is to assess volcanic activity across the surface of Venus  (Smrekar et al. , 2022). This will be accomplished using the VEM instrument to search for elevated thermal emission associated with active volcanism, and the VISAR instrument to detect topographic changes caused by recent/active flows. Synergistic surface observations from the VERITAS and EnVision missions will also aid in the search of active volcanism. Therefore, understanding the rate at which new lava flows may be emplaced and cool is important for mission planning, science requirements, and data observations.
Acknowledgments This research was supported through the  NASA   Solar System Workings (SSW) program  (Grant  80NSSC19K0547 ). The authors would like to thank  Scott Rowland ,  Steve Baloga , and an anonymous reviewer for their insightful reviews. The authors would also like to thank  Tracy Gregg  and  David Crown  for their constructive discussions relating to Venus's volcanism. This is Laboratory of Excellence ClerVolc contribution no. 576.
For example, one way to argue that a lexeme (set) has been borrowed into Timor-Alor-Pantar languages is to demonstrate that it has a Proto Austronesian (pan) or Proto Malayo-Polynesian (pmp) reconstructed form with a similar form and meaning, from which it can be regularly derived. Similarly, to argue that a lexeme attested in an Austronesian language is from a non-Austronesian (Papuan) sl, it is useful to show a similar form that has been reconstructed for a non-Austronesian group of languages. For the etymology of Austronesian lexemes, the database of Austronesian and its subgroups as listed in  Blust & Trussel (2016)  is used. In addition, several chapters in this volume make use of recent reconstructions of lower-level subgroups within Malayo-Polynesian that have been proposed in recent years: the Flores-Lembata subgroup, and within it, the Lamaholot subgroup  (Fricke 2019) ; the Central Flores subgroup  (Elias 2018) ; the Timor-Babar subgroup and the Central Timor subgroup (Proto Timor-Babar being a sister to Proto Central Timor and Helong, Edwards 2018b; 2018a); the Rote-Meto cluster  (Edwards 2021 ) and the Alorese cluster  (Sulistyono 2022).
However, in most of the regions discussed in this volume, linguistic documentation only started about fifty years ago, with the bulk of the work taking place during the last twenty years. So, most chapters use synchronic data sets without information on past stages of the languages. Apart from the fact that they are mostly synchronic in nature, the data sets as used in the studies of this volume are very different in type and size, an overview is given in Table  1. 1. Three contributions  (Klamer; Fricke; Moro et al. )  have made use of the data in the online lexical database LexiRumah  (Kaiping, Edwards & Klamer 2019). The reader is referred to Lexirumah for the sources of the data. Intuitively, we might expect that the size of a data set would influence the results: the more lexemes of a language are investigated, the higher the chance of detecting new loanwords.