dataesr/scientific-paragraphs-categorization huggingface dataset:
e. piezometers-according to the aim of the modeller. Indeed, to improve streamflow simulation and forecast, the additional information brought to the model should be relevant. For this work, we created a database of streamflow and groundwater level time series from 107 catchments and 355 piezometers, spread throughout mainland France and we computed annual low-flow and high-flow statistics. Through a simple correlation study, we assessed whether groundwater signal is representative of low flows, high flows or none of them. The dataset Figure  1. The 14 groups of catchment/piezometers pairs with the spatial extents of associated aquifers, according to the BDLISA  [Brugeron et al. , 2018]  national reference map. Only formations regarded as permeable by BDLISA are shown, which can hide some local aquifer formations, especially bedrock formations.
Presentation of the dataset The French mainland territory hosts a wide diversity of climatic and geological contexts, which induces a large variety of hydrological and hydrogeological configurations and behaviours, as shown in Figure  1. The largest aquifers are located in two major sedimentary basins, the Paris basin and the Aquitaine basin, which host piles of secondary and tertiary formations. The Paris basin Late Cretaceous chalk aquifer and the tertiary limestone Beauce aquifer are among the largest ones in Europe, with major concerns about water use conflicts during droughts or groundwater-induced floods  [Pinault et al. , 2005 , Lalot et al. , 2015]. On the outer parts of the Paris basin, smaller aquifers such as Perche Cenomanian sands and Vosges Triassic sandstones are also crucial resources for drinking water supply or biodiversity support in rivers.
These regional sedimentary aquifers are generally monitored by a network of long-term piezometers. Alluvial plains also host relevant and monitored aquifers, such as the Alsace alluvium or the Bresse graben gravels. Finally, regions in which the geology is dominated by metamorphic and plutonic formations, such as Britanny, host small local aquifers in fractured bedrock, some of which are monitored and can therefore be taken into account for the present study. Data were taken from two national databases managed by the Ministère de la Transition Écologique (MTE): Banque Hydro  [Leleu et al. , 2014 , Brigode et al. , 2020 , Delaigue et al. , 2021]  for streamflow and ADES  [Chery and Cattan, 2003 , Chery et al. , 2008 , BRGM, 2021]  for groundwater level. Thousands of measurement points are available in these databases, with significant differences in data quality and time extent: an initial selection through visual inspection of time series was made to eliminate points with less than 20 years of available data and af- fected by anthropogenic influence, such as dams or major withdrawals for catchments and known significant pumping for piezometers-modelling the influence of human activities on catchments is outside the scope of the present study.
Catchments in which more than 10% of precipitations fall as snow were also discarded, to avoid taking into account the memory effect of the snow cover. After this first selection, catchment/piezometer pairs were created. First, each piezometer was assigned to a formation of the French national hydrogeological reference database, BDLISA  [Brugeron et al. , 2018]. Then, for each catchment, only piezometers whose hydrogeological formation is outcropping within the catchment borders were selected. Along with the criterion of 20 years of available data with less than 10% of missing points, a contemporaneity criterion was added: streamflow and groundwa-ter level time series must have at least 10 years in common of available data, with less than 10% of missing points. Streamflow data are available at daily time step and groundwater level are available with variable time steps-daily, 10 days or monthly; for the study, all data were aggregated at monthly time steps.
In order to reach regionally relevant conclusions, 14 groups of catchment/piezometers pairs were created, with homogeneous geological characteristics. Aggregated formations of BDLISA were used as grouping factors, but larger groups had to be created to avoid groups that are too small. In particular, Triassic and bedrock formations, despite having major differences in geological characteristics, were merged as a miscellaneous group of old rocks aquifers. The chalk aquifer of the Paris basin, which represents the majority of catchment/piezometer pairs due to the exceptional availability of monitoring data on its outcropping area, was split into 5 regional groups with homogeneous geological descriptors. The resulting groups are shown in Figure  1.
[2018] -which limits their interactions with rivers, especially in small catchments like the ones studied in the database. The Dauphiny molasses aquifer has an exceptionally high permeability  [Dubar et al. , 1994] , which makes it reach the highest correlation values of the groups studied. The Paris basin Jurassic aquifers are mostly karstified in their outcropping areas  [Nicod, 1995] , with a quick response to flood events and little ability to store water and support low flows, which explains their better correlation with floods. The Beauce aquifer, which represents the majority of points in the Paris basin tertiary group, has a known role in supporting low flows  [Monteil, 2011] , which explains the exceptionally high correlation observed for drought indicators, but a more ambiguous role for floods, with a broader distribution correlation for QM X A and zM X A.
Despite being based on the aquifer division and categorisation in the BDLISA database  [Brugeron et al. , 2018] , the group classification used in the present study is imperfect, since the group choice was influenced by data availability. It is clear that groups with a too-wide diversity of geological con-texts, such as the two Aquitaine basin groups or the miscellaneous Triassic and bedrock aquifers, have the widest distributions of correlation values. No clear trend can be highlighted for these groups, while for more homogeneous ones-such as the regional chalk groups-less equivocal conclusions can be drawn. Data availability also has an influence on the correlation values: even though the dataset creation criterion of 10 years of contemporaneous data between streamflow and groundwater level, cited in Section 2, avoids computing correlations on a toosmall number of points, higher values of Spearman correlations are more likely to be reached on 10 points than on longer time series.
Conclusion In this article, we used a national database of streamflow and groundwater level data to assess the relationship between these two physical quantities, through a correlation study between yearly extrema indicators. Results show that in most cases, the intensity of groundwater level events is well correlated with the magnitude of droughts and floods, with large spatial heterogeneity. Subgroup analysis according to the geological context shows clearer patterns: some regional-scale aquifers have a univocal response to both low-flow and high-flow events, while others respond only to one type of event, and some do not seem to follow a trajectory that can be linked to streamflow events. Although it is very simple, without any modelling hypothesis, the analysis provides indications as to whether groundwater level data are likely to add useful information to a hydrological model, using a relatively small number of data.
The chalk area may also benefit from modelling approaches using groundwater level information, but not in all regions. It is also noteworthy that several aquifers, despite being of major importance for regional water resources, exhibit equivocal relationships with surface waterfor instance Cenomanian Perche sands and Vosges Triassic sandstones. The database and data gathering represents the largest part of the present work and we intend to share it as openly as possible to facilitate more thorough analyses. In particular, the correlation computation of yearly indicators hides the lag between groundwater level and streamflow extrema. Preliminary results that are not detailed here show that most piezometers are late with respect to streamflow, i. e. droughts and floods happen before low and high groundwater levels.
The database may also be used to conduct a large sample evaluation of groundwater/river coupled modelling approaches, in order to develop generalisable tools for operational hydrological simulations and forecasts. As a final recommendation, we encourage the development of longterm and high-frequency groundwater level measurements in gauged catchments, for surface hydrologists to be able to conduct thorough coupled modelling studies. We would like to thank Delphine Allier (BRGM) for the help in selecting the test dataset and Jean-Baptise Boissonnat (INRAE Antony) and Benoît Génot (INRAE Antony, now at U. R. B. S. ) for the database maintenance. We extend our warmest thanks to Dr. Léonard Santos (INRAE Antony) and Dr. Paul Royer-Gaspard for their careful proofreading that considerably improved the article.
Acknowledgements. DCMIP2016 is sponsored by the  National Center for Atmospheric Research Computational Information Systems Laboratory , the  Department of Energy Office of Science  (award no. DE-SC0016015 ), the  National Science Foundation  (award no. 1629819 ), the  National Aeronautics and Space Administration  (award no. NNX16AK51G ),the  National Oceanic and Atmospheric Administration Great Lakes Environmental Research Laboratory  (award no. NA12OAR4320071 ), the  Office of Naval Research and CU Boulder Research Computing. This work was made possible with support from our student and postdoctoral participants:  Sabina Abba Omar ,  Scott Bachman ,  Amanda Back ,  Tobias Bauer ,  Vinicius Capistrano ,  Spencer Clark ,  Ross Dixon ,  Christopher Eldred ,  Robert Fajber ,  Jared Ferguson ,  Emily Foshee ,  Ariane Frassoni ,  Alexander Goldstein ,  Jorge Guerra ,  Chasity Henson ,  Adam Herrington ,  Tsung-Lin Hsieh ,  Dave Lee ,  Theodore Letcher ,  Weiwei Li ,  Laura Mazzaro ,  Maximo Menchaca ,  Jonathan Meyer ,  Farshid Nazari ,  John O'Brien ,  Bjarke Tobias Olsen ,  Hossein Parishani ,  Charles Pelletier ,  Thomas Rackow ,  Kabir Rasouli ,  Cameron Rencurrel ,  Koichi Sakaguchi ,  Gökhan Sever ,  James Shaw ,  Konrad Simon ,  Abhishekh Srivastava ,  Nicholas Szapiro ,  Kazushi Takemura ,  Pushp Raj Tiwari ,  Chii-Yun Tsai ,  Richard Urata ,  Karin van der Wiel ,  Lei Wang ,  Eric Wolf ,  Zheng Wu ,  Haiyang Yu ,  Sungduk Yu  and  Jiawei Zhuang.
Code and data availability. Information on the availability of source code for the models featured in this paper can be found in Ullrich et al. (2017). For this particular test, the initialization routine, microphysics code, and sample plotting scripts are available at https://doi. org/10. 5281/zenodo. 1298671  (Ullrich et al. , 2018). Data used in this study will be uploaded to Dryad upon publication.
Separate approaches (perhaps combining model and long or paleo datasets) may be able to estimate scenario probability (or plausibility). This strategy can be widely applied; for example in the expert elicitation case of  Dessai et al. (2018) , impacts were expressed conditional on (unknown) changes in moisture advection into a the study region, the probabilities of which could in turn be estimated given other global-change scenarios. This approach of separating impact from probability could also be useful for some compound events and event cascades, where the conditional probability of one event given another can be estimated, although uncertainties inflate when estimating chains of events. Quantifying HiLo probabilities has been a serious challenge. For example although some individual studies proposed quantitative probabilities for extreme sea level rise this century  (DeConto et al.
The resulting dataset thereby links the ratio of pollination to herbivory at the singularity ‚ s ƒ" … * s ƒ † I * ‡ t ƒ * ˆ to the type of selection (Fig. 3a ). Stabilizing, runaway and disruptive selections are characterized by contrasting pollination to herbivory ratios. The ratio explains around two-thirds of the variance in selection type (Kruskal-Wallis,  vsB‰J < 2. 10 QV^). High pollination is largely associated with stabilizing selection, high herbivory with runaway selection, while disruptive selection happens for intermediate situations (Fig. 3a ). These results notably imply that the convergence of evolutionary singularities (i. e. convergence stability, Eshel 1983) is favored by pollination and disfavored by herbivory. Disruptive selection requires a balance between pollination and herbivory because strong herbivory relative to pollination fosters invasibility (inequality (4)), but convergence is lost when herbivory is too strong, leading to runaway dynamics (Fig.
001; Shapiro-Wilk test), and, therefore, a onetailed Wilcoxon test was used to identify regions of repetitive element enrichment across chromosomes. Subtelomere bounds were calculated on a per-chromosome end basis using auto_sub. py (https://github. com/tbrann99/Subtelomere). This script identi es repeat element enrichment by calculating p-values in a sliding ve-window mean at chromosome ends. A subtelomeric region was de ned as a region at the chromosome termini with a ve-window mean p-value less than 0. 1 and a penalty score less than 10. The penalty-based scoring system helps to remove instances of spurious repetitive element enrichment far from the termini being classi ed as subtelomeric. This is done by counting instances in which the ve-window mean is greater than 0. 5 (non-repetitive element enrichment) whilst scanning for the subtelomere.
We then ltered the remaining hits to remove low-quality alignments using BISER's total alignment error metric, requiring a value lower than 70% total alignment error. SDs were then categorised as subtelomeric -where at least one locus within the pair was subtelomeric; or chromosome body, where both loci fell within the chromosome body (classi ed by subtel. py, https://github. com/tbrann99/Subtelomere). Hits were visualised in a circular plot, in which the ideogram was annotated with subtelomere bounds. Segmental duplication coverage for respective regions was calculated using bedtools coverage and compared using a t-test. Expected values for the number of SDs occurring in different chromosomal regions were derived from a random distribution of SDs around the genome, excluding the Z and W speci c regions.
sc-RNASeq analysis All single-cell RNA-seq (scRNA-seq) data used in this study was from previous studies detailed in Table  1. Analysis was completed using equivalent methodology to that used in the respective associated publications with minor changes described below. Sequencing reads were mapped to the S. mansoni genome (V10) and gene annotation available in WormBase ParaSite release 18 (48) using cellranger 7. 0. 1 (49) (Supplementary File 10). Although a newer genome version was used, gene annotations remain largely unchanged (Supplementary File 1). Data analysis on the mapped reads was performed using Seurat  (50). Quality control, including ltering based on percentage of mitochondrial genes, number of transcripts, and number of genes identi ed per cell (Supplementary File 10), was performed separately for each dataset and biological sample and subsequently integrated.
Sporocyst samples had fewer cells, and therefore, less stringent ltering was applied. In these cases, scDblFinder (v1. 14. 0) (51) (https://github. com/plger/scDblFinder) with default parameters was used to remove multiplets (multiple cells in a single droplet) from the data. Elbow plots and clustree  (52)  were used to identify the optimal number of principal component elements and resolution of the Louvain algorithm, respectively. Adult samples were treated as a single dataset for analysis, irrespective of maturity and gender. Marker genes were identi ed by ROC (Receiver Operating Characteristic) analysis and were used, alongside manual ltering of undistinguished clusters and the original publications, for cluster identi cation (Supplementary File 10). For visualisation by pheatmap  (42) , cell type clusters were simpli ed by aggregating similar types (e.
Characterising the 'hypothetical protein' cluster Hypothetical protein gene models were visualised with gggenes (v0. 5. 0) (53) and ggplot2 (54) packages implemented in R  (30). Gene_viz. py (https://github. com/tbrann99/Subtelomere) was used to reformat the annotation (Supplementary File 1) for the gggenes package. Exons were coloured by their order of appearance in the transcript and aligned by their start codon for all sequences (bar seven lacking the canonical rst two exons). These additional seven genes were aligned at the third exon position and coloured to re ect exon number plus two, demonstrating their similarity to the 'full length' gene models. All gene models were represented in the direction of transcription. Hypothetical protein sequences were aligned using muscle (v5. 1) with default parameters  (55)  (Supplementary File 11) and a dendrogram was constructed from this alignment using IQ-Tree (56) with 1000 iterations of ultrafast bootstrapping  (57).
The resulting tree le was visualised on the Interactive Tree of Life (ITOL) (58) web tool. Conserved protein domains were identi ed using InterProScan5 Representational State Transfer API  (59) , and the tsv annotation le generated was processed with anno_domain_viz. py (https://github. com/tbrann99/Subtelomere) to generate ITOL-compatible protein domain annotations. Phobius (60) annotations were redundant with those from TmHelix (TMHMM2. 0) (61) and were removed. Amino acid alignment was used to generate the hypothetical protein dendrogram to search a protein database of reference proteomes using hmmsearch (HmmerWeb version 2. 41. 2 (62), with default parameters. Brie y, hmmsearch uses a protein alignment or pro le Hidden Markov model (HMM) as a query and performs a homology search against a protein database.
Using this approach versus a single sequence homology search improves sensitivity and improves identi cation of conserved residues across more distantly related sequences. Alignments to a Plexin-Semaphorin-Integrin (PSI) domain (PF01437) were visualised using the previously generated amino acid alignment in Jalview (63), where residues were coloured using clustal if the percentage identity was greater than 80%. Sequences with large gaps or that were fragmented were removed from the visualisation. The already identi ed domains at the 5' and 3' end were partially trimmed. A residue error plot provided by AlphaFold (DB version 2022-11-01) (64, 65) for Smp_173350. 1 (one of the few full-length S. mansoni hypothetical proteins with a putative PSI-domain included in Alphafold, due to the very recent annotation of a majority of subtelomeric genes) was visualised alongside putative domains to identify resolved structures.
SDs are present at 13 of the 15 de ned subtelomeres (not present at one end of both chromosomes 1 and 3). We validated this observed enrichment of subtelomeric SDs in two ways. Firstly, we compared the total SD coverage over the newly de ned subtelomeres and chromosome bodies (Fig. 2B , p = 0. 02; t-test), and, secondly, we analysed the number of SDs observed in these regions (Fig. 2C ,   (45) (46) (47). Gene clusters shown are those with more than two genes and found predominantly at the subtelomere. Genes are normalised by Z-score per row for bulk and the three life stages scRNA-seq values separately and also per dataset/lifestage for scRNAseq. X 2 = We explored composition of SDs and identi ed 154 genes overlapping these regions. Using an amino acid sequence similarity network approach, we de ned discrete gene clusters that, given their high sequence similarity, could have a putative shared function (Fig.
3A , Supplementary File 8). We describe clusters of "hypothetical proteins'' (n = 49; later renamed as 'plexin domain-containing proteins' -see next section), annexins (n = 17) and endoglycoceramidases (n = 15), whose gene members are expanded across the subtelomere and to a lesser extent, into the chromosome body. Smaller clusters are entirely subtelomeric, including conserved oligomeric golgi subunit 4 (n = 8) and mitochondrial aspartate tRNA ligase (n = 6). Clusters of cercarial proteases (n = 23) and mucins (n = 5) were also found. However, these two sets of genes are tandemly duplicated outside the subtelomere and were not analysed further (Supplementary Fig. 6 ). Finally, four sets of subtelomeric gene pairs were identi ed, and 23 genes did not have su cient amino acid similarity to any other genes in the dataset (Supplementary File 13).
Consistent with the bulk RNA-seq, limited expression was observed in the adult life stages despite the presence of a tegument. 4. 4 A subtelomere-expanded cluster of plexin domaincontaining genes show extensive sequence diversity and tegument-restricted expression To investigate the extent of gene diversity within clusters, we compared gene model structures within each cluster (Supplementary Figs. 7 to 11). We observed that all gene clusters have extensive gene model variation, fragmentation or truncation. Analysis of the full complement of subtelomeric-expanded gene families is outside the scope of this work. However, to illustrate the complexity of gene structures in this dynamic genomic region, we analysed the largest cluster of 49 "hypothetical proteins'' using a combination of database searches and an omics approach to illuminate potential protein function.
Thirty-ve of the 49 encoded proteins have an N-terminal signal peptide suggesting cell secretion/excretion, while 28 of these 35 also have a C-terminal membrane-bound domain suggesting cell surface retention. A protein domain search using InterproScan (59) could not identify any signi cant matches for the internal approximately 300 amino acid section found between the signal peptide and the membrane-bound domain. However, multiple sequence alignment of these proteins suggested the presence of highly conserved residues (Fig. 4B ) that formed a resolved structure (Fig. 4C ). To explore the possibility of any as yet unannotated domains within this resolved, conserved protein core, we used the alignment to search for similar protein sequences using pro le-HMMs (62). We identi ed 109 Plexin Sema Integrin (PSI) domains (PF01437) and a further 31 hits to proteins with "Plexin'' in their product description, despite no conserved domain annotation (p < 0.
01, Supplementary File 15), all of which are found outside the Schistosoma genus. These hits were present across distinct taxa, including 90 Actinopterdi (ray-nned sh) and 13 Insecta. The location of the PSI domain contained in the hypothetical proteins was identi ed by aligning the PSI (PF01437) seed sequences to the hypothetical protein cluster's multiple sequence alignment (Supplementary File 16). This was annotated onto the existing alignment and includes a set of conserved cysteines and a CxWC motif found in plexin repeats (Fig. 4B , Green). Therefore, we modelled the protein's tertiary structure to explore the regions corresponding to unknown domains. Alphafold has yet to be updated with the most recent S. mansoni protein predictions used in this analysis, and many proteins are, therefore, either unavailable or incorrectly fragmented.
However, one of the genes in the cluster of hypothetical proteins, Smp_173350, was present in full length in the Alphafold database and was used to infer structural information regarding the wider cluster. The predicted aligned error plot (Fig. 4C ) indicates the accuracy of the relative position of residues across the protein structure. The internal portion of this protein, between the signal peptide and membrane-bound domain, appears to form a single, high-con dence structure, in which the relative positions of these residues at the core of the protein have been resolved. Whilst the PSI domain (green in Fig. 4 ) occupies a portion of the protein core, a larger but highly structured portion of the protein has no similarity with known protein domains and remains uncharacterised (Fig. 4D ).