Find research datasets worth reusing

openogl-uk-3.0Apr 2022View details →

PRIMAVERA European winter windstorm event set

PRIMAVERA was a European Union Horizon 2020 project whose primary aim was to generate advanced and well-evaluated high-resolution global climate model datasets, for the benefit of governments, business and society in general.  Following consultation with members of the insurance industry, we have used a PRIMAVERA multi-model ensemble to generate a European winter windstorm event set for use in insurance risk analysis, containing approximately 1300 years of windstorm data. The uploaded dataset contains the model and re-analysis windstorm footprints in netcdf format and documentation of the data.  Further information is given in Lockwood et al., Using high-resolution global climate models from the PRIMAVERA project to create a European winter windstorm event set, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2022-12, in review, 2022. Any products or applications which use this dataset must state the following attribution “Acknowledgment to the PRIMAVERA partners. The information/material contained has been produced with funding from the European Union’s Horizon 2020 Research & Innovation Programme under grant agreement no. 641727.”

opencc-by-4.0Apr 2022View details →

European Stillbirth Rate Time Series Dataset

This dataset contains mostly annual time series of stillbirth rates from the mid-eighteenth century to the present for six countries including previously unpublished data for Denmark and for the Dutch region of Zeeland. There are several sheets within the Excel file, one of which explains the source of each series, potential stillbirth registration problems for each series and articles or book chapters with further information. This data was compiled by Eric Schneider from disparate sources and would not be possible without contributions from Anne Løkke (University of Copenhagen) and Frans van Poppel (NIDI).

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Whole-genome analysis of multiple wood ant population pairs supports similar speciation histories, but different degrees of gene flow, across their European ranges

The application of demographic history modelling and inference to the study of divergence between species has become a cornerstone of speciation genomics. Speciation histories are usually reconstructed by analysing single populations from each species, assuming that the inferred population history represents the actual speciation history. However, this assumption may not be met when species diverge with gene flow, e.g., when secondary contact may be confined to specific geographic regions. Here, we tested whether divergence histories inferred from heterospecific populations may vary depending on their geographic locations, using the two wood ant species Formica polyctena and F. aquilonia. We performed whole-genome resequencing of 20 individuals sampled in multiple locations across the European ranges of both species. Then, we reconstructed the histories of distinct heterospecific population pairs using a coalescent-based approach. Our analyses always supported a scenario of divergence with gene flow, suggesting that divergence started in the Pleistocene (ca. 500 kya) and occurred with continuous asymmetrical gene flow from F. aquilonia to F. polyctena until a recent time, when migration became negligible (2-19 kya). However, we found support for contemporary gene flow in a sympatric pair from Finland, where the species hybridise, but no signature of recent bidirectional gene flow elsewhere. Overall, our results suggest that divergence histories reconstructed from a few individuals may be applicable at the species level. Nonetheless, the geographical context of populations chosen to represent their species should be taken into account, as it may affect estimates of migration rates between species when gene flow is spatially heterogeneous.

opencc-zeroMay 2022View details →

Habitat quality for European Eel in Agder county over time

Results from method development for mapping habitat quality for European Eel

opencc-by-4.0Mar 2022View details →

The transmission of pottery technology amongst prehistoric European hunter-gatherers: code and data

Included in this paper are the data files which enable the main analytical findings of the paper to be reproduced. Some aspects of the spatial-temporal modelling will heavily depend on the user’s configuration and the digital elevation model available, so intermediate data that support the main conclusions of the paper have been included in the data repository.

Maps of ecosystem multifunctionality and ecological connectivity for identifying Green Infrastructure networks in the European Alps

High resolution raster datasets (20 meters) containing the results of an ecological connectivity and an ecosystem multifunctionality assessment for identifying Green Infrastructure networks in 10 pilot regions of the European Alps, modelled as part of the LUIGI Interreg Alpine Space project. Pilot regions include: department of Isère (FR), departments of Savoie and Haute-Savoie (FR), Munich Metropolitan Region (DE), Central Area of Salzburg (AT), South Burgenland (AT), Gori&scaron;ka region (SI), South Tyrol (IT), canton of Grisons (CH), Metropolitan City of Milan (IT), and Metropolitan City of Turin (IT). For a preview of the data and the results available for each pilot region <a href="https://www.alpine-space.org/projects/luigi/en/project-results/d.t1.2.1-pilot-regions-policy-briefs">click here</a> Further information on the LUIGI project is available at: <a href="https://www.alpine-space.org/projects/luigi/en/home">https://www.alpine-space.org/projects/luigi/en/home</a> <a href="https://webassets.eurac.edu/31538/1661510408-luigi-wp1-technical-annex-mapping-a-green-infrastructure-network-in-the-alpine-space.pdf">https://webassets.eurac.edu/31538/1661510408-luigi-wp1-technical-annex-mapping-a-green-infrastructure-network-in-the-alpine-space.pdf </a> The datasets include: <ul> <li>a map for ecosystem service-based multifunctionality calculated out of the average of 11 standardized ecosystem service indicators: water provision, crop potential, timber production, fodder provision, pollination potential, carbon sequestration, nitrogen retention, natural hazard mitigation, runoff retention, outdoor recreation, and landscape aesthetics.</li> <li>a map of the modelled Ecological Network composed of core areas and ecological corridors. Corridors are modelled for medium-large forest mammal species and represent least-cost pathways connecting core areas. Different classes indicate areas with different levels of current ecological connectivity starting from core areas to areas in cities or anthropized land with no connectivity. Modeled corridors are presented in two classes to mirror different levels of prioritization and management actions.</li> <li>a map of the resistance of the landscape to the movement of forest mammal species. The landscape resistance raster has been developed by reclassifying and aggregating a high resolution (5m) land use and land cover map. Resistance values have been determined in relation to the naturalness of different land use and land cover classes. In this context, land use or landscape resistance is intended as the opposite of habitat suitability.</li> </ul>

opencc-zeroNov 2019View details →

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Data from: Comparative crystallography suggests Maniraptoran theropod affinities for latest cretaceous European 'geckoid' eggshell

Thin fossil eggshells from Upper Cretaceous deposits of Europe, characterized by nodular ornamentation similar to modern gekkotan eggshells, have mostly been interpreted as gekkotan (='geckoid') in origin. However, in some cases, like the oogenus Pseudogeckoolithus, their theropod affinity was also suggested. The true affinity of these fossil 'geckoid' eggshells remained controversial due to the absence of analytical methods effective in identifying genuine gecko eggshells in the fossil record. In this study, we apply electron backscatter diffraction (EBSD) analysis to latest Cretaceous European 'geckoid' (including Pseudogeckoolithus) eggshells, in comparison with modern gekkotan and theropod (avian) eggshells. Our results show that Pseudogeckoolithus has a definite theropod eggshell-like crystallographic configuration, in clear contrast to that seen in modern geckos. Furthermore, the crystallography of the nodular ornamentation in Pseudogeckoolithus is comparable to that seen in megapode eggshells, but different from that of gecko eggshells, despite superficial morphological similarity. The remarkable morphological similarities between Pseudogeckoolithus and modern gecko eggshells are thus convergent, and the 'gekkotan affinity' hypothesis can be dismissed for Pseudogeckoolithus. This study provides a template for differentiating true gekkotan from dinosaurian eggshells in the fossil record. The potential functional significance of eggshell ornamentation, lost in most modern birds, requires further study, and experimental zoological approach may shed light on this issue. Finally, our results caution about the dangers of using potentially homoplastic eggshell characters in eggshell parataxonomy.

Population of European Countries

Population of European Countries on the first day of the year. This indicator is a reduced and interpreted verison of the Eurostat [<a href="https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=demo_pjan&lang=en">demo_pjan</a>] data asset.  It contains the total population for both sexes. Missing values, for example, in Kosovo, are estimated with linear interpolation.  Not yet know values are forecasted.

Figure 4 Mandible and p4 comparison for several European amphycionids. The red circle indicates the p4 in A new gigantic carnivore (Carnivora, Amphicyonidae) from the late middle Miocene of France

Figure 4 Mandible and p4 comparison for several European amphycionids. The red circle indicates the p4 position on the mandible. Modified from Dehm (1950), Kuss (1965), Bergounioux & Crouzel (1973), Viranta (1996), Peigné & Heizmann (2003), Peigné et al. (2008), Nagel, Stefen & Morlo (2009), Morales et al. (2021a) and Morales et al. (2021b). NMB TD1162 (Heizmannocyon steinheimensis), NMB SO4377 (Megamphicyon giganteus). The scale bar is five cm for the mandibles. The p4 are not to scale. Full-size DOI: 10.7717/peerj.13457/fig-4

opencc-by-4.0Dec 2020View details →

Multiple Partitioning of Multiplex Signed Networks: Application to European Parliament Votes

Presentation. For more than a decade, graphs have been used to model the voting behavior taking place in parliaments. However, the methods described in the literature suffer from several limitations. The two main ones are that 1) they rely on some temporal integration of the raw data, which causes some information loss; and/or 2) they identify groups of antagonistic voters, but not the context associated with their occurrence. In this article, we propose a novel method taking advantage of multiplex signed graphs to solve both these issues. It consists in first partitioning separately each layer, before grouping these partitions by similarity. We show the interest of our approach by applying it to a European Parliament dataset. Particularly, we study the voting behavior of French and Italian MEPs on "Agriculture and Rural Development" (AGRI) during the 2012-13 legislative year. These are the data used in the following paper: <ul> <li>N. Arınık, R. Figueiredo, and V. Labatut, “Multiple partitioning of multiplex signed networks: Application to European Parliament votes,” Social Networks, vol. 60, pp. 83–102, 2020. DOI: <a href="http://doi.org/10.1016/j.socnet.2019.02.001">10.1016/j.socnet.2019.02.001</a> ⟨<a href="https://hal.archives-ouvertes.fr/hal-02082574">hal-02082574</a>⟩</li> </ul> Source code. The code source is accessible on GitHub: <a href="https://github.com/CompNet/MultiNetVotes">https://github.com/CompNet/MultiNetVotes</a> Citation. If you use these data our this source code, please cite the above paper. <code>@Article{Arinik2020,</code> <code>  author    = {Arınık, Nejat and Figueiredo, Rosa and Labatut, Vincent},</code> <code>  title     = {Multiple Partitioning of Multiplex Signed Networks: Application to {E}uropean {P}arliament Votes},</code> <code>  journal   = {Social Networks},</code> <code>  year      = {2020},</code> <code>  volume    = {60},</code> <code>  pages     = {83-102},</code> <code>  doi       = {10.1016/j.socnet.2019.02.001},</code> <code>}</code> ---------------------------------------------- Details. # RAW INPUT FILES The 'itsyourparliament' folder contains all raw input files for further data processing. This is the same raw data that can be found in our previous Figshare repository: https://doi.org/10.6084/m9.figshare.5785833 The folder structure is as follows: * itsyourparliament/ ** domains: There are 28 domain files. Each file corresponds to a domain (such as Agriculture, Economy, etc.) and contains corresponding vote identifiers and their "itsyourparliament.eu" links. ** meps: There are 870 Members of Parliament (MEP) files. Each file contains the MEP information (such as name, country, address, etc.) ** votes: There are 7513 vote files. Each file contains the votes expressed by MEPs # ROLLCALL NETWORKS This folder contains two separate zip files regarding rollcall networks: - rollcall-networks: This folder contains only the rollcall networks that are used in the article. - all-rollcall-networks: For those who are interested in other countries or domains, we make available all rollcall networks that we can extract from raw data. Note that these rollcall networks constitute the layers of the input signed multplex network, as illustrated in Figure 1 of the article. Note also that we consider three vote types in our network extraction process: FOR, AGAINST and ABSTAIN. # ROLLCALL PARTITIONS Note that MEPs who voted similarly are connected together by positive links, and are connected by negative links to MEPs that voted differently from them. MEPs who did not vote at all (ABSENT) are isolates (nodes without any neighbor). We identify the factions of similarly voting MEPs in the graph by solving the Correlation Clustering problem (CC). The rollcall partitions correspond to voting patterns, as illustrated in Figure 1 of the article. # ROLLCALL CLUSTERING This folder contains the results of Steps 3 and 4 of our workflow (see Figure 1 in the article). The structure of this folder is as follows: |__ votetypes=FAA/: 'FAA' means we consider three vote types in our analysis: FOR, AGAINST and ABSTAIN. |__ F.purity-k=2-sil=SILHOUETTE_SCORE |__ clu=CLUSTER_NO/ |__ network: It corresponds to the network created through the similarity network-based approach, as explained in Section 4.4 of the article. |__ partition: It corresponds to the characteristic voting pattern, as explained in Section 4.4 of the article. ---------------------------------------------- Funding: this research benefited from the support of the Agorantic FR 3621, as well as the FMJH Program PGMO and from the support to this program from EDF-THALES-ORANGE-CRITEO.

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Transcript- and annotation-guided genome assembly of the European starling

The European starling, Sturnus vulgaris, is an ecologically significant, globally invasive avian species that is also suffering from a major decline in its native range. Here, we present the genome assembly and long-read transcriptome of an Australian-sourced European starling (S. vulgaris vAU), and a second North American genome (S. vulgaris vNA), as complementary reference genomes for population genetic and evolutionary characterisation. S. vulgaris vAU combined 10x Genomics linked-reads, low-coverage Nanopore sequencing, and PacBio Iso-Seq full-length transcript scaffolding to generate a 1050 Mb assembly on 1,628 scaffolds (72.5 Mb scaffold N50). Species-specific transcript mapping and gene annotation revealed high structural and functional completeness (94.6% BUSCO completeness). Further scaffolding against the high-quality zebra finch (Taeniopygia guttata) genome assigned 98.6% of the assembly to 32 putative nuclear chromosome scaffolds. Rapid, recent advances in sequencing technologies and bioinformatics software have highlighted the need for evidence-based assessment of assembly decisions on a case-by-case basis. Using S. vulgaris vAU, we demonstrate how the multifunctional use of PacBio Iso-Seq transcript data and complementary homology-based annotation of sequential assembly steps (assessed using a new tool, SAAGA) can be used to assess, inform, and validate assembly workflow decisions. We also highlight some counter-intuitive behaviour in traditional BUSCO metrics, and present BUSCOMP, a complementary tool for assembly comparison designed to be robust to differences in assembly size and base-calling quality. Finally, we present a second starling assembly, S. vulgaris vNA, to facilitate comparative analysis and global genomic research on this ecologically important species.

opencc-zeroJul 2022View details →

opencc-by-4.0Nov 2020View details →

COVID-19 mortality correlation with cloudiness, sunlight, latitude in European countries

"COVID-19 mortality correlation with cloudiness, sunlight, latitude in European countries" Dataset for preprint titled  "COVID-19 mortality: positive correlation with cloudiness but no correlation with sunlight and latitude in Europe" https://doi.org/10.1101/2021.01.27.21250658  by SECIL OMER, ADRIAN IFTIME, VICTOR BURCEA Corresponding author: A. Iftime, University of Medicine and Pharmacy "Carol Davila", Biophysics Department, 8 Blvd. Eroii Sanitari, 050474 Bucharest, Romania. Email address: adrian.iftime [at] umfcd.ro.   =========== Dataset file:  2.0.0.COVID-19_Mortality_Cloudiness_Insolation_EUROPE_March_December_2020.csv Dataset graphical preview:  2.0.0.INFOGRAPHIC_CloudFraction_vs_COVID-19_mortality_Europe_March-December_2020.png DATASET: 444 rows (records), with the following fields: "Country" :     Country name; 37 European countries included. "Date":      Date stamp at the collection time.     Data collection was performed in the last day of every month.      Date format: YYYY-MM-DD "Month_Key" :      Date stamp at the collection time, formatted for easier monthly time series analysis.     Date format: YYYY-MM "Month_Fct2020"     Date stamp at the collection time,formatted for easier graphing, as a string with names of the months     (in English).  "Deaths_per_1Mpop" :     Monthly mortality from COVID-19 raported in the country,      reported as number of COVID-19 deaths per 1 million population of the country,      in that particular month / country.      NB: it is reported as million population, not patients.  "LogDeaths_per_1Mpop" :     Log10 transformation of "Deaths_per_1Mpop" "Insolation_Average" :     Insolation average (solar irradiance at ground level),     in that particular month / country.      It is expressed in Watt / square meter of the ground surface.      Data derived from data avaialble at NASA Langley Research Center, NASA’s Earth Observatory,      CERES / FLASHFlux team, 2020,      https://neo.gsfc.nasa.gov/view.php?datasetId=CERES_INSOL_M     (old link: https://neo.sci.gsfc.nasa.gov/view.php?datasetId=CERES_INSOL_M ) "Cloud_Fraction" :     Cloudiness (also known as cloud fraction, cloud cover, cloud amount or sky cover),     as decimal fraction of the sky obscured by clouds,      in that particular month / country.      Data derived from NASA Goddard Space Flight Center, NASA’s Earth Observatory,     MODIS Atmosphere Science Team, 2020,      https://neo.gsfc.nasa.gov/view.php?datasetId=MODAL2_M_CLD_FR     (old link: https://neo.sci.gsfc.nasa.gov/view.php?datasetId=MODAL2_M_CLD_FR  ) "CENTR_latitude" and "CENTR_longitude" :     Latitude and Longitude of the country centroid, for each country.      Data derived from Google LLC, "Dataset publishing language: country centroids",     https://developers.google.com/public-data/docs/canonical/countries_csv         NOTE: This is identical in every month (obviuously);      it is redundantly included for easier monthly sectional analysis of the data.   =========== Versioning of the dataset:  MAJOR: changes yearly; 1 = 2020 MINOR: changes if new monthly data is added in that particular year.  PATCH: Changes only if errors or minor edits were performed.  =========== CHANGELOG:  Version 2.0.0.COVID-19_Mortality_Cloudiness_Insolation_EUROPE_March_December_2020.csv - CERES/FLASHFLUX data for August-December 2020 became available at new links at nasa.gov - These data were gathered, analyzed and introduced in this dataset (2.0.0).  - updated links for CERES/FLASHFLUX and MODIS dataset - added DOI link for preprint - minor edits on text.  -Dataset file source for this version (internal analysis source file): db_covid_all-ANALYSIS.2020-all-year_versiunea18d.csv Version 1.0.0.COVID-19_Mortality_Cloudiness_Insolation_EUROPE_March_August_2020.csv  First version Dataset file source for this version (internal analysis source file): db_covid_all-ANALYSIS.2020-09-22_r10.csv

opencc-by-4.0Dec 2021View details →

Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and East Asian ancestries

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions, and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Cross-tissue analyses indicated that over a third of effector genes most likely act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis, and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies. The data submitted here are expression and methylation models with LD reference data for the transcriptome-wide (TWAS), methylome-wide (MWAS) and transcript isoform-wide association study (TIsWAS) as described in the manuscript "Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and East Asian ancestries". Details of the methods are presented in the method section and supplementary information file.  TWAS analysis  Gene expression models for the six in-house expression datasets were generated using the PredictDB v7 pipeline for a total of 1,077 participants. Elastic net model building with 10-fold cross-validation was performed independently for each dataset. The elastic net models for GTEx v8 Colon Transverse were obtained from the PredictDB data repository (<a href="http://predictdb.org/">http://predictdb.org/</a>) and had been generated using the same pipeline. Models were computed using HapMap2 SNPs ±1Mb from each gene, together with covariate factors estimated using PEER32, clinical covariates when appropriate (age, sex and, where appropriate, case-control status, type of polyp and anatomic location in the colorectum), and three PCs from the individual dataset’s SNP genotype data. Transcript-based TWAS analyses (TIsWAS) were likewise performed by using transcript-level data from the SOCCS, BarcUVa-Seq and GTEx Colon Transverse datasets. MWAS analysis  Methylation beta values were calculated based on the manufacturer’s standard, ranging from 0 to 1. Quality control and data normalization were performed in R using the ChAMP software pipeline for the EPIC and 450K arrays. Briefly, we filtered out failed probes with detection P > 0.02 in >5% of samples, probes with <3 reads in >5% of samples per probe and all non-CpG probes. Samples with failed probes >0.1 were also excluded from downstream analyses. We discarded all probes with SNPs within 10bp of the interrogated CpG (from 1,000 Genomes Project, CEU population)34, and probes that ambiguously mapped to multiple locations in the human genome with up to two mismatches33. We only considered probes mapping to autosomes and those overlapping between the EPIC and the 450K arrays. Normalization was achieved using the Beta MIxture Quantile (BMIQ) method. Per probe methylation models were created using the PredictDB pipeline on the normalized methylation matrix and the genotypes as per TWAS eQTL analysis. To optimize power, we restricted our analysis to 263,341-238,443 (for the 450K array) and 377,678 (for the EPIC array) probes annotated to Islands, Shores and Shelves, and discarded “Open Sea” regions.

Fig. 9 in Two new species of the genus Siro Latreille, 1796 (Opiliones, Cyphophthalmi, Sironidae) in the European fauna

Fig. 9. Siro ozimeci Karaman sp. nov., holotype, ♀ (GMV 100066). A. Chelicerae, medial view.B. Pedipalp, medial view. C. Basitarsus and telotarsus, leg I. D. Basitarsus and telotarsus, leg IV. Scale bars = 100 µm.

Fig. 2 in Two new species of the genus Siro Latreille, 1796 (Opiliones, Cyphophthalmi, Sironidae) in the European fauna

Fig. 2. Bayesian inference topology of the combined dataset (18S, 28S, 16S, COI; 4936 bp) of Sironidae Simon, 1879 comprised of 38 taxa. Posterior probabilities> 90 are shown close to nodes. Coloured branches refer to different genera.

Fig. 5 in Two new species of the genus Siro Latreille, 1796 (Opiliones, Cyphophthalmi, Sironidae) in the European fauna

Fig. 5. Siro franzi Karaman & Raspotnig sp. nov. A–E. Paratype, ♂ (IKC1538). F–G. Paratype, ♀ (NHMW 28759). A. Chelicerae, medial view. B. Pedipalp, medial view. C. Basitarsus and telotarsus, leg I. D. Basitarsus and telotarsus, leg IV. E. Adenostyle. F. Basitarsus and telotarsus, leg I. G. Basitarsus and telotarsus, leg IV. Scale bars: A–D, F–G = 100 µm; E = 20 µm.

Fig. 4 in Two new species of the genus Siro Latreille, 1796 (Opiliones, Cyphophthalmi, Sironidae) in the European fauna

Fig. 4. Siro franzi Karaman & Raspotnig sp. nov. A, C, E. Paratype, ♂ (IKC1538). B, D, F. Paratype, ♀ (NHMW 28759). A–B. Dorsum. C–D. Ventral prosomal complex. E. Anal region, subventral view. F. Anal region, ventral view.

Fig. 1 in Two new species of the genus Siro Latreille, 1796 (Opiliones, Cyphophthalmi, Sironidae) in the European fauna

Fig. 1. Distribution of species of Siro Latreille, 1796 in Europe. Shaded areas: the maximum extent of glacial ice in north Europe and Alps during the Pleistocene; dashed line: extension of the northern part of the Adriatic Sea in the early Pliocene.

Fig. 8 in Two new species of the genus Siro Latreille, 1796 (Opiliones, Cyphophthalmi, Sironidae) in the European fauna

Fig. 8. Siro ozimeci Karaman sp. nov. A. Paratype, ♂ (GMV 100067). B–E. Holotype, ♀ (GMV 100066). F. Siro franzi Karaman & Raspotnig sp. nov. (IKC1538). A–B. Dorsum. C. Ventral prosomal complex. D. Anal region, ventral view. E–F. Spiracle.

Fig. 7 in Two new species of the genus Siro Latreille, 1796 (Opiliones, Cyphophthalmi, Sironidae) in the European fauna

Fig. 7. Siro franzi Karaman & Raspotnig sp. nov., paratype, ♀ (NHMW 28759). Distal portion of ovipositor, ventral view. Scale bar = 50 µm.