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569 results for “APRIL”
DeepFish Dataset (April 2022 update)
<p>Image bank of fish trays collected in the wholesale fish market in El Campello (Alicante, Spain) by artisanal fishing belonging to the <a href="http://deepfish.dtic.ua.es/">DeepFish project</a>.</p> <p>The original fish tray images are provided in the "<strong>fish_tray_images_2021_<em>MM</em>_<em>DD</em>.zip</strong>" files. MM and DD stand for the month and <em>initial</em> day (e.g. 04_01 stands for the first of April and subsequent days, and 05_17 stands for the 17th of May, and subsequent days until the end of the month). The last zip file of this kind, <strong>2021_06-09</strong>, contains all images from June to September.</p> <p>JSON files (in <strong>fish_tray_json_labels.zip</strong>) are prepared to be used with the "Django Labeller" software, but can be converted to any format, e.g. "COCO" which is also provided in the "<strong>coco_format_fish_data.json</strong>" file.</p> <p>Each of these JSON files is composed by an object containing the name of the image and the labels appearing in it. Inside each label, the following information is provided:</p> <ul> <li>Type of label. It can be a size (total, diameter of the eye...), tray or fish specie.</li> <li>Class of the label. It means the concrete specie, measurement or tray depending on the type of label.</li> <li>Semantic segmentation represented by one or multiple regions in case of occlusions. Represented by an array of coordinates in the image (x and y).</li> <li>Object_id: Identifier of the label, unique in the entire dataset.</li> <li>Father_object_id: In case this is not the main object (The label with the segmentation of the species). It will point to the identifier (ID) of that main species to which it belongs. It means, if this is the total size, it will point to the fish sized like that.</li> </ul> <p>Furthermore, estimated fish sizes are also provided in the "<strong>size_estimation_homography_DeepFish.csv</strong>" file. These size estimations are calculated using homography of the known tray size, to convert from pixel units to centimetres.</p>
Time series data of COVID-19 cases (rT-PCR-confirmed), hospitalisations (laboratory-confirmed), and hospital-associated deaths (laboratory confirmed) in South Africa, by imputed dates of symptom onset, from the start of the pandemic in March 2020 through April 2022.
<p>Time series data of COVID-19 cases (rT-PCR-confirmed), hospitalisations (laboratory-confirmed), and hospital-associated deaths (laboratory confirmed) in South Africa, by imputed dates of symptom onset, from the start of the pandemic in March 2020 through April 2022. These data were used to estimate the time-varying reproduction number (R) in South Africa, as described in https://www.medrxiv.org/content/10.1101/2022.07.22.22277932v1.full.</p>
NT1D CHU 7.850 MHz from April 8, 2024 Solar Eclipse
<p><em>Note:</em> NT1D collected data on multiple frequencies.</p> <p>7.850 MHz USB. Icom IC-7610 connected to dipole. PC is Dell Inspiron 5567 Windows 10</p>
EOL Dynamic Hierarchy Trunk (trunk): Dynamic Hierarchy Trunk 25 April 2017
This is the trunk for the EOL reference hierarchy. It determines the relationships among the higher taxa and adds a few taxa that are not covered by other resources. The EOL DH trunk is maintained in [TTT](<p></p>http://ttt.biodinfo.org/) developed by Colin (Congtian Lin) and Jiangning Wang from Biodiversity Informatics Group of the Institute of Zoology, Chinese Academy of Sciences. ##References Adl, S. M., et al. 2019. Revisions to the classification, nomenclature, and diversity of eukaryotes. Journal of Eukaryotic Microbiology 66, 4–119. <p></p>https://doi.org/10.1111/jeu.12691 Aguiar, A.P., Deans, A.R., Engel, M.S., Forshage, M., Huber, J.T., Jennings, J.T., Johnson, N.F., Lelej, A.S., Longino, J.T., Lohrmann, V., Mikó, I., Ohl, M., Rasmussen, C., Taeger, A., Yu, D.S.K., 2013. Order Hymenoptera . In : Zhang, Z.-Q. (Ed.) Animal Biodiversity: An Outline of Higher-level Classification and Survey of Taxonomic Richness (Addenda 2013). Zootaxa 3703, 51–62. <p></p>https://doi.org/10.11646/zootaxa.3703.1.12 Aspöck, U., Haring, E., Aspöck, H., 2012. The phylogeny of the Neuropterida: long lasting and current controversies and challenges (Insecta: Endopterygota). Arthropod Systematics & Phylogeny 70, 119–129. Benton, M., 2014. Vertebrate Palaeontology. John Wiley & Sons. Betancur-R, R., Wiley, E.O., Arratia, G., Acero, A., Bailly, N., Miya, M., Lecointre, G., Ortí, G., 2017. Phylogenetic classification of bony fishes. BMC Evolutionary Biology 17, 162. <p></p>https://doi.org/10.1186/s12862-017-0958-3 Bleidorn, Christoph. 2019. Recent Progress in Reconstructing Lophotrochozoan (Spiralian) Phylogeny." Organisms Diversity & Evolution 19, no. 4 (December 1, 2019): 557–66. <p></p>https://doi.org/10.1007/s13127-019-00412-4. Bouchard, P., Bousquet, Y., Davies, A., Alonso-Zarazaga, M., Lawrence, J., Lyal, C., Newton, A., Reid, C., Schmitt, M., Slipinski, A., Smith, A., 2011. Family-Group Names In Coleoptera (Insecta). ZooKeys 88, 1–972. <p></p>https://doi.org/10.3897/zookeys.88.807 Cannon, Johanna Taylor, Bruno Cossermelli Vellutini, Julian Smith, Fredrik Ronquist, Ulf Jondelius, and Andreas Hejnol. 2016. Xenacoelomorpha Is the Sister Group to Nephrozoa. Nature 530(7588):89–93. <p></p>https://doi.org/10.1038/nature16520. Davis, R.B., Baldauf, S.L., Mayhew, P.J., 2010. The origins of species richness in the Hymenoptera: insights from a family-level supertree. BMC Evolutionary Biology 10, 109. <p></p>https://doi.org/10.1186/1471-2148-10-109 Dunlop, J. A., Penney, D. & Jekel, D. 2015. A summary list of fossil spiders and their relatives. In World Spider Catalog. Natural History Museum Bern, online at <p></p>http://wsc.nmbe.ch Dunn, C.W., Giribet, G., Edgecombe, G.D., Hejnol, A., 2014. Animal Phylogeny and Its Evolutionary Implications. Annu. Rev. Ecol. Evol. Syst. 45, 371–395. <p></p>https://doi.org/10.1146/annurev-ecolsys-120213-091627 Foottit, R. G., Adler, P. H., eds. 2017. Insect Biodiversity: Science and Society, Volume 1 & 2. 2nd Edition. Wiley-Blackwell. Fritz, U., Havaš, P., 2013. Order Testudines: 2013 update. In : Zhang, Z.-Q. (Ed.) Animal Biodiversity: An Outline of Higher-level Classification and Survey of Taxonomic Richness (Addenda 2013). Zootaxa 3703, 12–14. <p></p>https://doi.org/10.11646/zootaxa.3703.1.4 Giribet, Gonzalo. 2016. New Animal Phylogeny: Future Challenges for Animal Phylogeny in the Age of Phylogenomics. Organisms Diversity & Evolution 16 (2):419–26. <p></p>https://doi.org/10.1007/s13127-015-0236-4. Giribet, Gonzalo, and Gregory D. Edgecombe. 2020. The Invertebrate Tree of Life. Princeton, United States: Princeton University Press, 2020. Guy, L., Ettema, T.J.G., 2011. The archaeal __TACK__ superphylum and the origin of eukaryotes. Trends in Microbiology 19, 580–587. <p></p>https://doi.org/10.1016/j.tim.2011.09.002 Hinchliff, C.E., Smith, S.A., Allman, J.F., Burleigh, J.G., Chaudhary, R., Coghill, L.M., Crandall, K.A., Deng, J., Drew, B.T., Gazis, R., Gude, K., Hibbett, D.S., Katz, L.A., Laughinghouse, H.D., McTavish, E.J., Midford, P.E., Owen, C.L., Ree, R.H., Rees, J.A., Soltis, D.E., Williams, T., Cranston, K.A., 2015. Synthesis of phylogeny and taxonomy into a comprehensive tree of life. PNAS 112, 12764–12769. <p></p>https://doi.org/10.1073/pnas.1423041112 Holzenthal, R.W., Morse, J.C., Kjer, K.M., 2011. Order Trichoptera Kirby, 1813. In: Zhang, Z.-Q. (Ed.) Animal biodiversity: An outline of higher-level classification and survey of taxonomic richness. Zootaxa 3148, 209. <p></p>https://doi.org/10.11646/zootaxa.3148.1.40 Hormiga, G., Griswold, C.E., 2014. Systematics, Phylogeny, and Evolution of Orb-Weaving Spiders. Annu. Rev. Entomol. 59, 487–512. <p></p>https://doi.org/10.1146/annurev-ento-011613-162046 James, S.W., Davidson, S.K., 2012. Molecular phylogeny of earthworms (Annelida:Crassiclitellata) based on 28S, 18S and 16S gene sequences. Invertebrate Systematics 26, 213. <p></p>https://doi.org/10.1071/IS11012 Jarvis, E.D., Mirarab, S., Aberer, A.J., Li, B., Houde, P., Li, C., Ho, S.Y.W., Faircloth, B.C., Nabholz, B., Howard, J.T., Suh, A., Weber, C.C., Fonseca, R.R. da, Li, J., Zhang, F., Li, H., Zhou, L., Narula, N., Liu, L., Ganapathy, G., Boussau, B., Bayzid, M.S., Zavidovych, V., Subramanian, S., Gabaldón, T., Capella-Gutiérrez, S., Huerta-Cepas, J., Rekepalli, B., Munch, K., Schierup, M., Lindow, B., Warren, W.C., Ray, D., Green, R.E., Bruford, M.W., Zhan, X., Dixon, A., Li, S., Li, N., Huang, Y., Derryberry, E.P., Bertelsen, M.F., Sheldon, F.H., Brumfield, R.T., Mello, C.V., Lovell, P.V., Wirthlin, M., Schneider, M.P.C., Prosdocimi, F., Samaniego, J.A., Velazquez, A.M.V., Alfaro-Núñez, A., Campos, P.F., Petersen, B., Sicheritz-Ponten, T., Pas, A., Bailey, T., Scofield, P., Bunce, M., Lambert, D.M., Zhou, Q., Perelman, P., Driskell, A.C., Shapiro, B., Xiong, Z., Zeng, Y., Liu, S., Li, Z., Liu, B., Wu, K., Xiao, J., Yinqi, X., Zheng, Q., Zhang, Y., Yang, H., Wang, J., Smeds, L., Rheindt, F.E., Braun, M., Fjeldsa, J., Orlando, L., Barker, F.K., Jønsson, K.A., Johnson, W., Koepfli, K.-P., O__Brien, S., Haussler, D., Ryder, O.A., Rahbek, C., Willerslev, E., Graves, G.R., Glenn, T.C., McCormack, J., Burt, D., Ellegren, H., Alström, P., Edwards, S.V., Stamatakis, A., Mindell, D.P., Cracraft, J., Braun, E.L., Warnow, T., Jun, W., Gilbert, M.T.P., Zhang, G., 2014. Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346, 1320–1331. <p></p>https://doi.org/10.1126/science.1253451 Kathirithamby, J., Engel, M.S., 2014. A Revised Key to the Living and Fossil Families of Strepsiptera, with the Description of a New Family, Cretostylopidae. Journal of the Kansas Entomological Society 87, 385–388. <p></p>https://doi.org/10.2317/JKES140407.1 Kjer, K.M., Simon, C., Yavorskaya, M., Beutel, R.G., 2016. Progress, pitfalls and parallel universes: a history of insect phylogenetics. Journal of The Royal Society Interface 13, 20160363. <p></p>https://doi.org/10.1098/rsif.2016.0363 Klopfstein, S., Vilhelmsen, L., Heraty, J.M., Sharkey, M., Ronquist, F., 2013. The Hymenopteran Tree of Life: Evidence from Protein-Coding Genes and Objectively Aligned Ribosomal Data. PLoS ONE 8, e69344. <p></p>https://doi.org/10.1371/journal.pone.0069344 Kocot, Kevin M., Torsten H. Struck, Julia Merkel, Damien S. Waits, Christiane Todt, Pamela M. Brannock, David A. Weese, et al. 2016. Phylogenomics of Lophotrochozoa with Consideration of Systematic Error. Systematic Biology, syw079. <p></p>https://doi.org/10.1093/sysbio/syw079. Laumer, Christopher E., Rosa Fernández, Sarah Lemer, David Combosch, Kevin M. Kocot, Ana Riesgo, Sónia C. S. Andrade, Wolfgang Sterrer, Martin V. Sørensen, and Gonzalo Giribet. 2019. Revisiting Metazoan Phylogeny with Genomic Sampling of All Phyla. Proceedings of the Royal Society B: Biological Sciences 286 (1906): 20190831. <p></p>https://doi.org/10.1098/rspb.2019.0831. Laumer, Christopher E., Nicolas Bekkouche, Alexandra Kerbl, Freya Goetz, Ricardo C. Neves, Martin V. Sørensen, Reinhardt M. Kristensen, et al. 2015. Spiralian Phylogeny Informs the Evolution of Microscopic Lineages. Current Biology 25(15): 2000–2006. <p></p>https://doi.org/10.1016/j.cub.2015.06.068. Leschen, R.A.B., Beutel, R.G., 2014. Morphology and Systematics: Phytophaga. Walter de Gruyter. Li, H., Shao, R., Song, N., Song, F., Jiang, P., Li, Z., Cai, W., 2015. Higher-level phylogeny of paraneopteran insects inferred from mitochondrial genome sequences. Scientific Reports 5. <p></p>https://doi.org/10.1038/srep08527 Lozano-Fernandez, J., Tanner, A.R., Giacomelli, M., Carton, R., Vinther, J., Edgecombe, G.D., Pisani, D., 2019. Increasing species sampling in chelicerate genomic-scale datasets provides support for monophyly of Acari and Arachnida. Nature Communications 10, 2295. <p></p>https://doi.org/10.1038/s41467-019-10244-7 Malm, T., Nyman, T., 2015. Phylogeny of the symphytan grade of Hymenoptera: new pieces into the old jigsaw(fly) puzzle. Cladistics 31, 1–17. <p></p>https://doi.org/10.1111/cla.12069 Marlétaz, Ferdinand, Katja T. C. A. Peijnenburg, Taichiro Goto, Noriyuki Satoh, and Daniel S. Rokhsar. 2019. A New Spiralian Phylogeny Places the Enigmatic Arrow Worms among Gnathiferans. Current Biology 29(2):312-318.e3. <p></p>https://doi.org/10.1016/j.cub.2018.11.042. Nakano, T., Ramlah, Z., Hikida, T., 2012. Phylogenetic position of gastrostomobdellid leeches (Hirudinida, Arhynchobdellida, Erpobdelliformes) and a new family for the genus Orobdella. Zoologica Scripta 41, 177–185. <p></p>https://doi.org/10.1111/j.1463-6409.2011.00506.x Naylor, G.J.P., Caira, J.N., Jensen, K.R.E., Rosana, K.M., Straube, N., Lakner, C., 2012. Elasmobranch Phylogeny: A Mitochondrial Estimate Based on 595 Species. In J.C. Carrier, J.A. Musick and M.R. Heithaus (editors), The Biology of Sharks and Their Relatives. 31-56. CRC Press, Taylor & Francis Group. Nesbitt, S.J., 2011. The Early Evolution of Archosaurs: Relationships and the Origin of Major Clades. Bulletin of the American Museum of Natural History, 2011(352):1-292. <p></p>https://doi.org/10.1206/352.1 Nesnidal, Maximilian P., Martin Helmkampf, Achim Meyer, Alexander Witek, Iris Bruchhaus, Ingo Ebersberger, Thomas Hankeln, Bernhard Lieb, Torsten H. Struck, and Bernhard Hausdorf. 2013. New Phylogenomic Data Support the Monophyly of Lophophorata and an Ectoproct-Phoronid Clade and Indicate That Polyzoa and Kryptrochozoa Are Caused by Systematic Bias. BMC Evolutionary Biology 13(1): 253. <p></p>https://doi.org/10.1186/1471-2148-13-253. Oaks, J.R., 2011. A Time-Calibrated Species Tree of Crocodylia Reveals a Recent Radiation of the True Crocodiles. Evolution 65, 3285–3297. <p></p>https://doi.org/10.1111/j.1558-5646.2011.01373.x Okamura, B., Gruhl, A., Reft, A.J., 2015. Cnidarian Origins of the Myxozoa, in: Okamura, B., Gruhl, A., Bartholomew, J.L. (Eds.), Myxozoan Evolution, Ecology and Development. Springer International Publishing, Cham, pp. 45–68. <p></p>https://doi.org/10.1007/978-3-319-14753-6_3 Pyron, R.A., Burbrink, F.T., Wiens, J.J., 2013. A phylogeny and revised classification of Squamata, including 4161 species of lizards and snakes. BMC Evolutionary Biology 13, 93. <p></p>https://doi.org/10.1186/1471-2148-13-93 Robertson, J.A., Ślipiński, A., Moulton, M., Shockley, F.W., Giorgi, A., Lord, N.P., Mckenna, D.D., Tomaszewska, W., Forrester, J., Miller, K.B., Whiting, M.F., Mchugh, J.V., 2015. Phylogeny and classification of Cucujoidea and the recognition of a new superfamily Coccinelloidea (Coleoptera: Cucujiformia): Systematics of Cucujoidea and Coccinelloidea. Systematic Entomology 40, 745–778. <p></p>https://doi.org/10.1111/syen.12138 Rouse, Greg W., Nerida G. Wilson, Jose I. Carvajal, and Robert C. Vrijenhoek. 2016. New Deep-Sea Species of Xenoturbella and the Position of Xenacoelomorpha. Nature 530(7588):94–97. <p></p>https://doi.org/10.1038/nature16545. Ruhfel, B.R., Gitzendanner, M.A., Soltis, P.S., Soltis, D.E., Burleigh, J.G., 2014. From algae to angiosperms–inferring the phylogeny of green plants (Viridiplantae) from 360 plastid genomes. BMC Evolutionary Biology 14, 23. <p></p>https://doi.org/10.1186/1471-2148-14-23 Schiffer, Philipp H., Helen E. Robertson, and Maximilian J. Telford. 2018. Orthonectids Are Highly Degenerate Annelid Worms. Current Biology 28(12):1970-1974.e3. <p></p>https://doi.org/10.1016/j.cub.2018.04.088. The Angiosperm Phylogeny Group, 2016. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 181, 1–20. <p></p>https://doi.org/10.1111/boj.12385 Van Nieukerken, E.J., Kaila, L., Kitching, I.J., Kristensen, N.P., Lees, D.C., Minet, J., Mitter, C., Mutanen, M., Regier, J.C., Simonsen, T.J., Wahlberg, N., Yen, S.-H., Zahiri, R., Adamski, D., Baixeras, J., Bartsch, D., Bengtsson, B.Å., Brown, J.W., Bucheli, S.R., Davis, D.R., Prins, J.D., Prins, W.D., Epstein, M.E., Gentili-Poole, P., Gielis, C., Hättenschwiler, P., Hausmann, A., Holloway, J.D., Kallies, A., Karsholt, O., Kawahara, A.Y., Koster, S.J.C., Kozlov, M.V., Lafontaine, J.D., Lamas, G., Landry, J.-F., Lee, S., Nuss, M., Park, K.-T., Penz, C., Rota, J., Schintlmeister, A., Schmidt, B.C., Sohn, J.-C., Solis, M.A., Tarmann, G.M., Warren, A.D., Weller, S., Yakovlev, R.V., Zolotuhin, V.V., Zwick, A., 2011. Order Lepidoptera Linnaeus, 1758. In: Zhang, Z.-Q. (Ed.) Animal biodiversity: An outline of higher-level classification and survey of taxonomic richness. Zootaxa 3148, 212. <p></p>https://doi.org/10.11646/zootaxa.3148.1.41 Vea, I.M., Grimaldi, D.A., 2015. Diverse New Scale Insects (Hemiptera: Coccoidea) in Amber from the Cretaceous and Eocene with a Phylogenetic Framework for Fossil Coccoidea. novi 2015, 1–15. <p></p>https://doi.org/10.1206/3823.1 Vélez-Zuazo, X., Agnarsson, I., 2011. Shark tales: A molecular species-level phylogeny of sharks (Selachimorpha, Chondrichthyes). Molecular Phylogenetics and Evolution 58, 207–217. <p></p>https://doi.org/10.1016/j.ympev.2010.11.018 Weigert, A., Bleidorn, C., 2016. Current status of annelid phylogeny. Org Divers Evol 16, 345–362. <p></p>https://doi.org/10.1007/s13127-016-0265-7 Weirauch, C., Schuh, R.T., 2011. Systematics and Evolution of Heteroptera: 25 Years of Progress. Annu. Rev. Entomol. 56, 487–510. <p></p>https://doi.org/10.1146/annurev-ento-120709-144833 Wiegmann, B.M., Trautwein, M.D., Winkler, I.S., Barr, N.B., Kim, J.-W., Lambkin, C., Bertone, M.A., Cassel, B.K., Bayless, K.M., Heimberg, A.M., Wheeler, B.M., Peterson, K.J., Pape, T., Sinclair, B.J., Skevington, J.H., Blagoderov, V., Caravas, J., Kutty, S.N., Schmidt-Ott, U., Kampmeier, G.E., Thompson, F.C., Grimaldi, D.A., Beckenbach, A.T., Courtney, G.W., Friedrich, M., Meier, R., Yeates, D.K., 2011. Episodic radiations in the fly tree of life. Proceedings of the National Academy of Sciences 108, 5690–5695. <p></p>https://doi.org/10.1073/pnas.1012675108 Winterton, S.L., Hardy, N.B., Wiegmann, B.M., 2010. On wings of lace: phylogeny and Bayesian divergence time estimates of Neuropterida (Insecta) based on morphological and molecular data. Systematic Entomology 35, 349–378. <p></p>https://doi.org/10.1111/j.1365-3113.2010.00521.x Yuri, T., Kimball, R.T., Harshman, J., Bowie, R.C.K., Braun, M.J., Chojnowski, J.L., Han, K.-L., Hackett, S.J., Huddleston, C.J., Moore, W.S., Reddy, S., Sheldon, F.H., Steadman, D.W., Witt, C.C., Braun, E.L., 2013. Parsimony and Model-Based Analyses of Indels in Avian Nuclear Genes Reveal Congruent and Incongruent Phylogenetic Signals. Biology 2, 419–444. <p></p>https://doi.org/10.3390/biology2010419 Zverkov, Oleg A., Kirill V. Mikhailov, Sergey V. Isaev, Leonid Y. Rusin, Olga V. Popova, Maria D. Logacheva, Alexey A. Penin, et al. 2019. Dicyemida and Orthonectida: Two Stories of Body Plan Simplification. Frontiers in Genetics 10. <p></p>https://doi.org/10.3389/fgene.2019.00443.<p></p>Updated dynamic hierarchy trunk. Ready for second Smasher run. The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
EOL Dynamic Hierarchy Trunk (trunk): Dynamic Hierarchy Trunk 24 April 2017
This is the trunk for the EOL reference hierarchy. It determines the relationships among the higher taxa and adds a few taxa that are not covered by other resources. The EOL DH trunk is maintained in [TTT](<p></p>http://ttt.biodinfo.org/) developed by Colin (Congtian Lin) and Jiangning Wang from Biodiversity Informatics Group of the Institute of Zoology, Chinese Academy of Sciences. ##References Adl, S. M., et al. 2019. Revisions to the classification, nomenclature, and diversity of eukaryotes. Journal of Eukaryotic Microbiology 66, 4–119. <p></p>https://doi.org/10.1111/jeu.12691 Aguiar, A.P., Deans, A.R., Engel, M.S., Forshage, M., Huber, J.T., Jennings, J.T., Johnson, N.F., Lelej, A.S., Longino, J.T., Lohrmann, V., Mikó, I., Ohl, M., Rasmussen, C., Taeger, A., Yu, D.S.K., 2013. Order Hymenoptera . In : Zhang, Z.-Q. (Ed.) Animal Biodiversity: An Outline of Higher-level Classification and Survey of Taxonomic Richness (Addenda 2013). Zootaxa 3703, 51–62. <p></p>https://doi.org/10.11646/zootaxa.3703.1.12 Aspöck, U., Haring, E., Aspöck, H., 2012. The phylogeny of the Neuropterida: long lasting and current controversies and challenges (Insecta: Endopterygota). Arthropod Systematics & Phylogeny 70, 119–129. Benton, M., 2014. Vertebrate Palaeontology. John Wiley & Sons. Betancur-R, R., Wiley, E.O., Arratia, G., Acero, A., Bailly, N., Miya, M., Lecointre, G., Ortí, G., 2017. Phylogenetic classification of bony fishes. BMC Evolutionary Biology 17, 162. <p></p>https://doi.org/10.1186/s12862-017-0958-3 Bleidorn, Christoph. 2019. Recent Progress in Reconstructing Lophotrochozoan (Spiralian) Phylogeny." Organisms Diversity & Evolution 19, no. 4 (December 1, 2019): 557–66. <p></p>https://doi.org/10.1007/s13127-019-00412-4. Bouchard, P., Bousquet, Y., Davies, A., Alonso-Zarazaga, M., Lawrence, J., Lyal, C., Newton, A., Reid, C., Schmitt, M., Slipinski, A., Smith, A., 2011. Family-Group Names In Coleoptera (Insecta). ZooKeys 88, 1–972. <p></p>https://doi.org/10.3897/zookeys.88.807 Cannon, Johanna Taylor, Bruno Cossermelli Vellutini, Julian Smith, Fredrik Ronquist, Ulf Jondelius, and Andreas Hejnol. 2016. Xenacoelomorpha Is the Sister Group to Nephrozoa. Nature 530(7588):89–93. <p></p>https://doi.org/10.1038/nature16520. Davis, R.B., Baldauf, S.L., Mayhew, P.J., 2010. The origins of species richness in the Hymenoptera: insights from a family-level supertree. BMC Evolutionary Biology 10, 109. <p></p>https://doi.org/10.1186/1471-2148-10-109 Dunlop, J. A., Penney, D. & Jekel, D. 2015. A summary list of fossil spiders and their relatives. In World Spider Catalog. Natural History Museum Bern, online at <p></p>http://wsc.nmbe.ch Dunn, C.W., Giribet, G., Edgecombe, G.D., Hejnol, A., 2014. Animal Phylogeny and Its Evolutionary Implications. Annu. Rev. Ecol. Evol. Syst. 45, 371–395. <p></p>https://doi.org/10.1146/annurev-ecolsys-120213-091627 Foottit, R. G., Adler, P. H., eds. 2017. Insect Biodiversity: Science and Society, Volume 1 & 2. 2nd Edition. Wiley-Blackwell. Fritz, U., Havaš, P., 2013. Order Testudines: 2013 update. In : Zhang, Z.-Q. (Ed.) Animal Biodiversity: An Outline of Higher-level Classification and Survey of Taxonomic Richness (Addenda 2013). Zootaxa 3703, 12–14. <p></p>https://doi.org/10.11646/zootaxa.3703.1.4 Giribet, Gonzalo. 2016. New Animal Phylogeny: Future Challenges for Animal Phylogeny in the Age of Phylogenomics. Organisms Diversity & Evolution 16 (2):419–26. <p></p>https://doi.org/10.1007/s13127-015-0236-4. Giribet, Gonzalo, and Gregory D. Edgecombe. 2020. The Invertebrate Tree of Life. Princeton, United States: Princeton University Press, 2020. Guy, L., Ettema, T.J.G., 2011. The archaeal __TACK__ superphylum and the origin of eukaryotes. Trends in Microbiology 19, 580–587. <p></p>https://doi.org/10.1016/j.tim.2011.09.002 Hinchliff, C.E., Smith, S.A., Allman, J.F., Burleigh, J.G., Chaudhary, R., Coghill, L.M., Crandall, K.A., Deng, J., Drew, B.T., Gazis, R., Gude, K., Hibbett, D.S., Katz, L.A., Laughinghouse, H.D., McTavish, E.J., Midford, P.E., Owen, C.L., Ree, R.H., Rees, J.A., Soltis, D.E., Williams, T., Cranston, K.A., 2015. Synthesis of phylogeny and taxonomy into a comprehensive tree of life. PNAS 112, 12764–12769. <p></p>https://doi.org/10.1073/pnas.1423041112 Holzenthal, R.W., Morse, J.C., Kjer, K.M., 2011. Order Trichoptera Kirby, 1813. In: Zhang, Z.-Q. (Ed.) Animal biodiversity: An outline of higher-level classification and survey of taxonomic richness. Zootaxa 3148, 209. <p></p>https://doi.org/10.11646/zootaxa.3148.1.40 Hormiga, G., Griswold, C.E., 2014. Systematics, Phylogeny, and Evolution of Orb-Weaving Spiders. Annu. Rev. Entomol. 59, 487–512. <p></p>https://doi.org/10.1146/annurev-ento-011613-162046 James, S.W., Davidson, S.K., 2012. Molecular phylogeny of earthworms (Annelida:Crassiclitellata) based on 28S, 18S and 16S gene sequences. 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Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346, 1320–1331. <p></p>https://doi.org/10.1126/science.1253451 Kathirithamby, J., Engel, M.S., 2014. A Revised Key to the Living and Fossil Families of Strepsiptera, with the Description of a New Family, Cretostylopidae. Journal of the Kansas Entomological Society 87, 385–388. <p></p>https://doi.org/10.2317/JKES140407.1 Kjer, K.M., Simon, C., Yavorskaya, M., Beutel, R.G., 2016. Progress, pitfalls and parallel universes: a history of insect phylogenetics. Journal of The Royal Society Interface 13, 20160363. <p></p>https://doi.org/10.1098/rsif.2016.0363 Klopfstein, S., Vilhelmsen, L., Heraty, J.M., Sharkey, M., Ronquist, F., 2013. The Hymenopteran Tree of Life: Evidence from Protein-Coding Genes and Objectively Aligned Ribosomal Data. PLoS ONE 8, e69344. <p></p>https://doi.org/10.1371/journal.pone.0069344 Kocot, Kevin M., Torsten H. Struck, Julia Merkel, Damien S. Waits, Christiane Todt, Pamela M. Brannock, David A. Weese, et al. 2016. Phylogenomics of Lophotrochozoa with Consideration of Systematic Error. Systematic Biology, syw079. <p></p>https://doi.org/10.1093/sysbio/syw079. Laumer, Christopher E., Rosa Fernández, Sarah Lemer, David Combosch, Kevin M. Kocot, Ana Riesgo, Sónia C. S. Andrade, Wolfgang Sterrer, Martin V. Sørensen, and Gonzalo Giribet. 2019. Revisiting Metazoan Phylogeny with Genomic Sampling of All Phyla. Proceedings of the Royal Society B: Biological Sciences 286 (1906): 20190831. <p></p>https://doi.org/10.1098/rspb.2019.0831. Laumer, Christopher E., Nicolas Bekkouche, Alexandra Kerbl, Freya Goetz, Ricardo C. Neves, Martin V. Sørensen, Reinhardt M. Kristensen, et al. 2015. Spiralian Phylogeny Informs the Evolution of Microscopic Lineages. Current Biology 25(15): 2000–2006. <p></p>https://doi.org/10.1016/j.cub.2015.06.068. Leschen, R.A.B., Beutel, R.G., 2014. Morphology and Systematics: Phytophaga. Walter de Gruyter. Li, H., Shao, R., Song, N., Song, F., Jiang, P., Li, Z., Cai, W., 2015. Higher-level phylogeny of paraneopteran insects inferred from mitochondrial genome sequences. Scientific Reports 5. <p></p>https://doi.org/10.1038/srep08527 Lozano-Fernandez, J., Tanner, A.R., Giacomelli, M., Carton, R., Vinther, J., Edgecombe, G.D., Pisani, D., 2019. Increasing species sampling in chelicerate genomic-scale datasets provides support for monophyly of Acari and Arachnida. Nature Communications 10, 2295. <p></p>https://doi.org/10.1038/s41467-019-10244-7 Malm, T., Nyman, T., 2015. Phylogeny of the symphytan grade of Hymenoptera: new pieces into the old jigsaw(fly) puzzle. Cladistics 31, 1–17. <p></p>https://doi.org/10.1111/cla.12069 Marlétaz, Ferdinand, Katja T. C. A. Peijnenburg, Taichiro Goto, Noriyuki Satoh, and Daniel S. Rokhsar. 2019. A New Spiralian Phylogeny Places the Enigmatic Arrow Worms among Gnathiferans. Current Biology 29(2):312-318.e3. <p></p>https://doi.org/10.1016/j.cub.2018.11.042. Nakano, T., Ramlah, Z., Hikida, T., 2012. Phylogenetic position of gastrostomobdellid leeches (Hirudinida, Arhynchobdellida, Erpobdelliformes) and a new family for the genus Orobdella. Zoologica Scripta 41, 177–185. <p></p>https://doi.org/10.1111/j.1463-6409.2011.00506.x Naylor, G.J.P., Caira, J.N., Jensen, K.R.E., Rosana, K.M., Straube, N., Lakner, C., 2012. Elasmobranch Phylogeny: A Mitochondrial Estimate Based on 595 Species. In J.C. Carrier, J.A. Musick and M.R. Heithaus (editors), The Biology of Sharks and Their Relatives. 31-56. CRC Press, Taylor & Francis Group. Nesbitt, S.J., 2011. The Early Evolution of Archosaurs: Relationships and the Origin of Major Clades. Bulletin of the American Museum of Natural History, 2011(352):1-292. <p></p>https://doi.org/10.1206/352.1 Nesnidal, Maximilian P., Martin Helmkampf, Achim Meyer, Alexander Witek, Iris Bruchhaus, Ingo Ebersberger, Thomas Hankeln, Bernhard Lieb, Torsten H. Struck, and Bernhard Hausdorf. 2013. 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BMC Evolutionary Biology 14, 23. <p></p>https://doi.org/10.1186/1471-2148-14-23 Schiffer, Philipp H., Helen E. Robertson, and Maximilian J. Telford. 2018. Orthonectids Are Highly Degenerate Annelid Worms. Current Biology 28(12):1970-1974.e3. <p></p>https://doi.org/10.1016/j.cub.2018.04.088. The Angiosperm Phylogeny Group, 2016. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 181, 1–20. <p></p>https://doi.org/10.1111/boj.12385 Van Nieukerken, E.J., Kaila, L., Kitching, I.J., Kristensen, N.P., Lees, D.C., Minet, J., Mitter, C., Mutanen, M., Regier, J.C., Simonsen, T.J., Wahlberg, N., Yen, S.-H., Zahiri, R., Adamski, D., Baixeras, J., Bartsch, D., Bengtsson, B.Å., Brown, J.W., Bucheli, S.R., Davis, D.R., Prins, J.D., Prins, W.D., Epstein, M.E., Gentili-Poole, P., Gielis, C., Hättenschwiler, P., Hausmann, A., Holloway, J.D., Kallies, A., Karsholt, O., Kawahara, A.Y., Koster, S.J.C., Kozlov, M.V., Lafontaine, J.D., Lamas, G., Landry, J.-F., Lee, S., Nuss, M., Park, K.-T., Penz, C., Rota, J., Schintlmeister, A., Schmidt, B.C., Sohn, J.-C., Solis, M.A., Tarmann, G.M., Warren, A.D., Weller, S., Yakovlev, R.V., Zolotuhin, V.V., Zwick, A., 2011. Order Lepidoptera Linnaeus, 1758. In: Zhang, Z.-Q. (Ed.) Animal biodiversity: An outline of higher-level classification and survey of taxonomic richness. Zootaxa 3148, 212. <p></p>https://doi.org/10.11646/zootaxa.3148.1.41 Vea, I.M., Grimaldi, D.A., 2015. Diverse New Scale Insects (Hemiptera: Coccoidea) in Amber from the Cretaceous and Eocene with a Phylogenetic Framework for Fossil Coccoidea. novi 2015, 1–15. <p></p>https://doi.org/10.1206/3823.1 Vélez-Zuazo, X., Agnarsson, I., 2011. Shark tales: A molecular species-level phylogeny of sharks (Selachimorpha, Chondrichthyes). Molecular Phylogenetics and Evolution 58, 207–217. <p></p>https://doi.org/10.1016/j.ympev.2010.11.018 Weigert, A., Bleidorn, C., 2016. Current status of annelid phylogeny. Org Divers Evol 16, 345–362. <p></p>https://doi.org/10.1007/s13127-016-0265-7 Weirauch, C., Schuh, R.T., 2011. Systematics and Evolution of Heteroptera: 25 Years of Progress. Annu. Rev. Entomol. 56, 487–510. <p></p>https://doi.org/10.1146/annurev-ento-120709-144833 Wiegmann, B.M., Trautwein, M.D., Winkler, I.S., Barr, N.B., Kim, J.-W., Lambkin, C., Bertone, M.A., Cassel, B.K., Bayless, K.M., Heimberg, A.M., Wheeler, B.M., Peterson, K.J., Pape, T., Sinclair, B.J., Skevington, J.H., Blagoderov, V., Caravas, J., Kutty, S.N., Schmidt-Ott, U., Kampmeier, G.E., Thompson, F.C., Grimaldi, D.A., Beckenbach, A.T., Courtney, G.W., Friedrich, M., Meier, R., Yeates, D.K., 2011. Episodic radiations in the fly tree of life. Proceedings of the National Academy of Sciences 108, 5690–5695. <p></p>https://doi.org/10.1073/pnas.1012675108 Winterton, S.L., Hardy, N.B., Wiegmann, B.M., 2010. On wings of lace: phylogeny and Bayesian divergence time estimates of Neuropterida (Insecta) based on morphological and molecular data. Systematic Entomology 35, 349–378. <p></p>https://doi.org/10.1111/j.1365-3113.2010.00521.x Yuri, T., Kimball, R.T., Harshman, J., Bowie, R.C.K., Braun, M.J., Chojnowski, J.L., Han, K.-L., Hackett, S.J., Huddleston, C.J., Moore, W.S., Reddy, S., Sheldon, F.H., Steadman, D.W., Witt, C.C., Braun, E.L., 2013. Parsimony and Model-Based Analyses of Indels in Avian Nuclear Genes Reveal Congruent and Incongruent Phylogenetic Signals. Biology 2, 419–444. <p></p>https://doi.org/10.3390/biology2010419 Zverkov, Oleg A., Kirill V. Mikhailov, Sergey V. Isaev, Leonid Y. Rusin, Olga V. Popova, Maria D. Logacheva, Alexey A. Penin, et al. 2019. Dicyemida and Orthonectida: Two Stories of Body Plan Simplification. Frontiers in Genetics 10. <p></p>https://doi.org/10.3389/fgene.2019.00443.<p></p>Updated dynamic hierarchy trunk. Removed additional taxa that are covered by subtrees from WoRMS, Species File Projects, IOC Birdlist, and other providers. The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
EOL Dynamic Hierarchy Trunk (trunk): Dynamic Hierarchy Trunk 26 April 2017
This is the trunk for the EOL reference hierarchy. It determines the relationships among the higher taxa and adds a few taxa that are not covered by other resources. The EOL DH trunk is maintained in [TTT](<p></p>http://ttt.biodinfo.org/) developed by Colin (Congtian Lin) and Jiangning Wang from Biodiversity Informatics Group of the Institute of Zoology, Chinese Academy of Sciences. ##References Adl, S. M., et al. 2019. Revisions to the classification, nomenclature, and diversity of eukaryotes. Journal of Eukaryotic Microbiology 66, 4–119. <p></p>https://doi.org/10.1111/jeu.12691 Aguiar, A.P., Deans, A.R., Engel, M.S., Forshage, M., Huber, J.T., Jennings, J.T., Johnson, N.F., Lelej, A.S., Longino, J.T., Lohrmann, V., Mikó, I., Ohl, M., Rasmussen, C., Taeger, A., Yu, D.S.K., 2013. Order Hymenoptera . In : Zhang, Z.-Q. (Ed.) Animal Biodiversity: An Outline of Higher-level Classification and Survey of Taxonomic Richness (Addenda 2013). Zootaxa 3703, 51–62. <p></p>https://doi.org/10.11646/zootaxa.3703.1.12 Aspöck, U., Haring, E., Aspöck, H., 2012. The phylogeny of the Neuropterida: long lasting and current controversies and challenges (Insecta: Endopterygota). Arthropod Systematics & Phylogeny 70, 119–129. Benton, M., 2014. Vertebrate Palaeontology. John Wiley & Sons. Betancur-R, R., Wiley, E.O., Arratia, G., Acero, A., Bailly, N., Miya, M., Lecointre, G., Ortí, G., 2017. Phylogenetic classification of bony fishes. BMC Evolutionary Biology 17, 162. <p></p>https://doi.org/10.1186/s12862-017-0958-3 Bleidorn, Christoph. 2019. Recent Progress in Reconstructing Lophotrochozoan (Spiralian) Phylogeny." Organisms Diversity & Evolution 19, no. 4 (December 1, 2019): 557–66. <p></p>https://doi.org/10.1007/s13127-019-00412-4. Bouchard, P., Bousquet, Y., Davies, A., Alonso-Zarazaga, M., Lawrence, J., Lyal, C., Newton, A., Reid, C., Schmitt, M., Slipinski, A., Smith, A., 2011. Family-Group Names In Coleoptera (Insecta). ZooKeys 88, 1–972. <p></p>https://doi.org/10.3897/zookeys.88.807 Cannon, Johanna Taylor, Bruno Cossermelli Vellutini, Julian Smith, Fredrik Ronquist, Ulf Jondelius, and Andreas Hejnol. 2016. Xenacoelomorpha Is the Sister Group to Nephrozoa. Nature 530(7588):89–93. <p></p>https://doi.org/10.1038/nature16520. Davis, R.B., Baldauf, S.L., Mayhew, P.J., 2010. The origins of species richness in the Hymenoptera: insights from a family-level supertree. BMC Evolutionary Biology 10, 109. <p></p>https://doi.org/10.1186/1471-2148-10-109 Dunlop, J. A., Penney, D. & Jekel, D. 2015. A summary list of fossil spiders and their relatives. In World Spider Catalog. Natural History Museum Bern, online at <p></p>http://wsc.nmbe.ch Dunn, C.W., Giribet, G., Edgecombe, G.D., Hejnol, A., 2014. Animal Phylogeny and Its Evolutionary Implications. Annu. Rev. Ecol. Evol. Syst. 45, 371–395. <p></p>https://doi.org/10.1146/annurev-ecolsys-120213-091627 Foottit, R. G., Adler, P. H., eds. 2017. Insect Biodiversity: Science and Society, Volume 1 & 2. 2nd Edition. Wiley-Blackwell. Fritz, U., Havaš, P., 2013. Order Testudines: 2013 update. In : Zhang, Z.-Q. (Ed.) Animal Biodiversity: An Outline of Higher-level Classification and Survey of Taxonomic Richness (Addenda 2013). Zootaxa 3703, 12–14. <p></p>https://doi.org/10.11646/zootaxa.3703.1.4 Giribet, Gonzalo. 2016. New Animal Phylogeny: Future Challenges for Animal Phylogeny in the Age of Phylogenomics. Organisms Diversity & Evolution 16 (2):419–26. <p></p>https://doi.org/10.1007/s13127-015-0236-4. Giribet, Gonzalo, and Gregory D. Edgecombe. 2020. The Invertebrate Tree of Life. Princeton, United States: Princeton University Press, 2020. Guy, L., Ettema, T.J.G., 2011. The archaeal __TACK__ superphylum and the origin of eukaryotes. 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The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
EOL Hierarchy Entries April 2017: Hierarchy Entries April 2017
This is a file listing all EOL hierarchy entries along with associated name strings, mapped taxon concept (EOL page ID), richness score of mapped page, and source hierarchy. Columns in the file: EOL_ID (taxon concept/page ID)|richness score|scientificName|hierarchy entry ID| source hierarchy
Cellularity & Growth Form Data Version April 2023
<p>Cellularity & growth form data derived from the following sources: </p> <p>Abdullin, S.R., Bagmet, V.B., Nikulin, A.Y., Nikulin, V.Y., Gorpenchenko, T.Y., Grishin, S.Y., Allaguvatova, R.Z. and Gontcharov, A.A., 2022. Emended description of the genus Eremochloris (Trebouxiophyceae, Chlorophyta), with Eremochloris kamchatica sp. nov. from Kamchatka, Russia. Phycologia, 61(2), pp.175-183. <a href="https://doi.org/10.1080/00318884.2021.2024710">https://doi.org/10.1080/00318884.2021.2024710</a></p> <p>Adl, S.M., Bass, D., Lane, C.E., Lukeš, J., Schoch, C.L., Smirnov, A., Agatha, S., Berney, C., Brown, M.W., Burki, F., Cárdenas, P., Čepička, I., Chistyakova, L., Campo, J. del, Dunthorn, M., Edvardsen, B., Eglit, Y., Guillou, L., Hampl, V., Heiss, A.A., Hoppenrath, M., James, T.Y., Karnkowska, A., Karpov, S., Kim, E., Kolisko, M., Kudryavtsev, A., Lahr, D.J.G., Lara, E., Gall, L.L., Lynn, D.H., Mann, D.G., Massana, R., Mitchell, E.A.D., Morrow, C., Park, J.S., Pawlowski, J.W., Powell, M.J., Richter, D.J., Rueckert, S., Shadwick, L., Shimano, S., Spiegel, F.W., Torruella, G., Youssef, N., Zlatogursky, V., Zhang, Q., 2019. Revisions to the Classification, Nomenclature, and Diversity of Eukaryotes. Journal of Eukaryotic Microbiology 66, 4–119. <a href="https://doi.org/10.1111/jeu.12691">https://doi.org/10.1111/jeu.12691</a></p> <p>Alberghina, J.S., Vigna, M.S., Confalonieri, V.A., 2006. Phylogenetic position of the Oedogoniales within the green algae (Chlorophyta) and the evolution of the absolute orientation of the flagellar apparatus. Plant Syst. Evol. 261, 151–163. <a href="https://doi.org/10.1007/s00606-006-0449-2">https://doi.org/10.1007/s00606-006-0449-2</a></p> <p>Amaral, R., Fawley, K.P., Němcová, Y., Ševčíková, T., Lukešová, A., Fawley, M.W., Santos, L.M. and Eliáš, M., 2020. Toward Modern Classification of Eustigmatophytes, Including the Description of Neomonodaceae Fam. Nov. and Three New Genera. Journal of Phycology, 56(3), pp.630-648. <a href="https://doi.org/10.1111/jpy.12980">https://doi.org/10.1111/jpy.12980</a></p> <p>Andersen, R.A., 1987. Synurophyceae classis nov., a new class of algae. American journal of botany, 74(3), pp.337-353. <a href="https://doi.org/10.2307/2443810">https://doi.org/10.2307/2443810</a></p> <p>Antonio, M., Schulze-Makuch, D., 2012. Toward a New Understanding of Multicellularity. Hypotheses in the Life Sciences 2, 4–14. <a href="http://www.hy-ls.org/index.php/hyls/article/view/89/0">http://www.hy-ls.org/index.php/hyls/article/view/89/0</a></p> <p>Arneson, R.D., 1973. Pseudotetracystis, a new chlorosarcinean alga. Journal of Phycology, 9(1), pp.10-14. <a href="https://doi.org/10.1111/j.1529-8817.1973.tb04056.x">https://doi.org/10.1111/j.1529-8817.1973.tb04056.x</a></p> <p>Aslam, Z., Shin, W., Kim, M.K., Im, W.T. and Lee, S.T., 2007. Marinichlorella kaistiae gen. et sp. nov.(Trebouxiophyceae, Chlorophyta) based on polyphasic taxonomy. Journal of Phycology, 43(3), pp.576-584. <a href="https://doi.org/10.1111/j.1529-8817.2007.00345.x">https://doi.org/10.1111/j.1529-8817.2007.00345.x</a></p> <p>Badewitz, H. (2004). The genus Microcorycia Cockerell, 1911 (Testacealobosia, Rhizopoda, Protozoa). A critical monograph of the genus including a first description of a new species: Microcorycia scutella n. sp. Lauterbornia 50: 111-146. </p> <p>Bakker, M.E., De Jong, Y.S. and Lokhorst, G.M., 1997. The flagellar apparatus ultrastructure in Leptosira erumpens (Deason & Bold) lukesová and its contribution to the understanding of phylogenese relationships within the microthamniales (chlorophyta). Archiv für Protistenkunde, 148(1-2), pp.17-31. <a href="https://doi.org/10.1016/S0003-9365(97)80033-4">https://doi.org/10.1016/S0003-9365(97)80033-4</a></p> <p>Barcytė, D., Hodač, L. and Nedbalová, L., 2017. Lunachloris lukesovae gen. et sp. nov.(Trebouxiophyceae, Chlorophyta), a novel coccoid green alga isolated from soil in South Bohemia, Czech Republic. European Journal of Phycology, 52(3), pp.281-291. <a href="https://doi.org/10.1080/09670262.2017.1283541">https://doi.org/10.1080/09670262.2017.1283541</a></p> <p>Barsanti, L., Frassanito, A.M., Passarelli, V., Evangelista, V., Etebari, M., Paccagnini, E., Lupetti, P., Lenzi, P., Verni, F. and Gualtieri, P., 2013. Tetraflagellochloris mauritanica gen. et sp. nov.(Chlorophyceae), a new flagellated alga from the mauritanian desert: morphology, ultrastructure, and phylogenetic framing. Journal of Phycology, 49(1), pp.178-193. <a href="https://doi.org/10.1111/j.1529-8817.2012.01232.x">https://doi.org/10.1111/j.1529-8817.2012.01232.x</a></p> <p>Bass, D., Chao, E.E.-Y., Nikolaev, S., Yabuki, A., Ishida, K., Berney, C., Pakzad, U., Wylezich, C., Cavalier-Smith, T., 2009. Phylogeny of Novel Naked Filose and Reticulose Cercozoa: Granofilosea cl. n. and Proteomyxidea Revised. Protist 160, 75–109. <a href="https://doi.org/10.1016/j.protis.2008.07.002">https://doi.org/10.1016/j.protis.2008.07.002</a></p> <p>Becker, B., Marin, B., 2009. Streptophyte algae and the origin of embryophytes. Annals of Botany 103, 999–1004. <a href="https://doi.org/10.1093/aob/mcp044">https://doi.org/10.1093/aob/mcp044</a></p> <p>Bernard, Catherine, Alastair G. B. Simpson & David J. Patterson (2000) Some free-living flagellates (protista) from anoxic habitats Ophelia 52(2):113-142. <a href="https://doi.org/10.1080/00785236.1999.10409422">https://doi.org/10.1080/00785236.1999.10409422</a></p> <p>Berney, C., Geisen, S., Van Wichelen, J., Nitsche, F., Vanormelingen, P., Bonkowski, M. and Bass, D., 2015. Expansion of the __reticulosphere__: diversity of novel branching and network-forming amoebae helps to define Variosea (Amoebozoa). Protist, 166(2):271-295. <a href="https://doi.org/10.1016/j.protis.2015.04.001">https://doi.org/10.1016/j.protis.2015.04.001</a></p> <p>Biard, T., 2022. 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Hiding in plain sight: Koshicola spirodelophila gen. et sp. nov.(Chaetopeltidales, Chlorophyceae), a novel green alga associated with the aquatic angiosperm Spirodela polyrhiza. American Journal of Botany, 103(5), pp.865-875. <a href="https://doi.org/10.3732/ajb.1500481">https://doi.org/10.3732/ajb.1500481</a></p> <p>Watanabe, S., Mitui, K., Nakayama, T. and Inouye, I., 2002. Phylogenetic analyses of the species of Chlorosarcinopsis and Neochlorosarcina (Chlorophyceae). Journal of Phycology, 38, pp.36-36. <a href="https://doi.org/10.1046/j.1529-8817.38.s1.103.x">https://doi.org/10.1046/j.1529-8817.38.s1.103.x</a></p> <p>Wetherbee, R. and Verbruggen, H., 2016. Kraftionema allantoideum, a new genus and family of Ulotrichales (Chlorophyta) adapted for survival in high intertidal pools. Journal of Phycology, 52(5), pp.704-715. <a href="https://doi.org/10.1111/jpy.12447">https://doi.org/10.1111/jpy.12447</a></p> <p>Wetherbee, R., Bringloe, T.T., Costa, J.F., van de Meene, A., Andersen, R.A. and Verbruggen, H., 2021. New pelagophytes show a novel mode of algal colony development and reveal a perforated theca that may define the class. Journal of Phycology, 57(2), pp.396-411. <a href="https://doi.org/10.1111/jpy.13074-20-137">https://doi.org/10.1111/jpy.13074-20-137</a></p> <p>Wetherbee, R., Jackson, C.J., Repetti, S.I., Clementson, L.A., Costa, J.F., van de Meene, A., Crawford, S. and Verbruggen, H., 2019. The golden paradox–a new heterokont lineage with chloroplasts surrounded by two membranes. Journal of phycology, 55(2), pp.257-278. <a href="https://doi.org/10.1111/jpy.12822">https://doi.org/10.1111/jpy.12822</a></p> <p>Wolf, M., Buchheim, M., Hegewald, E., Krienitz, L. and Hepperle, D., 2002. Phylogenetic position of the Sphaeropleaceae (Chlorophyta). Plant Systematics and Evolution, 230(3), pp.161-171. <a href="https://doi.org/10.1007/s006060200002">https://doi.org/10.1007/s006060200002</a></p> <p>Wujek, D.E. The first occurrence of the coccoid green alga Borodinella polytetras. Miller in North America (Michigan). Great Lakes Bot. 59(3-4):94-98. <a href="http://hdl.handle.net/2027/spo.0497763.0058.107">http://hdl.handle.net/2027/spo.0497763.0058.107</a></p> <p>Wujek, D.E., 2016. The chlorococcalean Green Alga Hydrianum Rabenhorst from North America (Kansas and Michigan). Transactions of the Kansas Academy of Science, 119(1), pp.105-108. <a href="https://www.jstor.org/stable/24887848">https://www.jstor.org/stable/24887848</a></p> <p>Yoon H.S. et al. (2016) Rhodophyta. In: Archibald J. et al. (eds) Handbook of the Protists. Springer, Cham. <a href="https://doi.org/10.1007/978-3-319-32669-6_33-1">https://doi.org/10.1007/978-3-319-32669-6_33-1</a></p>
Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021
<p>These are data from the CorporateMix US study rounds 1-4. Below is a description of the files:</p> <p>1. participants: this contains a list of all the study participants for each round. EaA unique participant identified by the participant_id and round.</p> <p>2. contacts: this contains the individuals with whom a participant had a contact.</p> <p>3.df_all: this is generated by merging the participant and contacts dataframes using the participant_id and round as primary keys.</p> <p>4. day_rd1: this is data for round 1 day of survey. The survey design for round 1 was different, so these data are important to distinguish between day 1 and day 2 contacts.</p>
MedSens data (Version 4.0.0, update April 23, 2023). Dataset maintained by Reef Check Italia
<p>MedSens data is a dataset including the abundance of selected Mediterranean marine species, collected by trained volunteers (<strong>EcoDivers</strong>, i.e. scuba divers, free divers and snorkelers) according to the <strong>Reef Check Mediterranean Underwater Coastal Environment Monitoring</strong> (<strong>RCMed U-CEM</strong>) protocol (Cerrano et al., 2017), and maintained by the non-profit association <strong>Reef Check Italia</strong>.</p> <p>This dataset is a subset of 25 selected species from the <strong>Reef Check Med - key Mediterranean marine species</strong> dataset, and it is specifically intended to calculate the <strong><em>MedSens </em></strong>index developed by Eva Turicchia, Carlo Cerrano, Matteo Ghetta, Marco Abbiati and Massimo Ponti (Turicchia et al., 2021). MedSens data is provided as ESRI shapefiles in WGS84 geographic coordinates (EPSG:4326).</p> <p> </p> <p><strong><em>MedSens </em>abstract</strong></p> <p>Citizen science (CS) projects may provide community-based ecosystem monitoring, expanding our ability to collect data across space and time. However, the data from CS are often not effectively integrated into institutional monitoring programs and decision-making processes, especially in marine conservation. This limitation is partially due to difficulties in accessing the data and the lack of tools and indices for proper management at intended spatial and temporal scales. <em>MedSens</em> is a biotic index specifically developed to provide information on the environmental status of subtidal rocky coastal habitats, filling a gap between marine CS and coastal management in the Mediterranean Sea. The <em>MedSens</em> index is based on 25 selected species, incorporating their sensitivities to the pressures indicated by the European Union’s Marine Strategy Framework Directive (MSDF) and open data on their distributions and abundances, collected by trained volunteers (mainly scuba divers, but also free divers and snorkelers) using the Reef Check Mediterranean Underwater Coastal Environment Monitoring (RCMed U-CEM) protocol. The species sensitivities were assessed relative to their resistance and resilience against physical, chemical, and biological pressures, according to benchmark levels and a literature review. The <em>MedSens</em> index was calibrated on a dataset of 33,021 observations from 569 volunteers (2001 to 2019), along six countries’ coasts. A free and user-friendly QGIS plugin allows easy index calculation for areas and time frames of interest. The <em>MedSens</em> index was applied to Mediterranean marine protected areas (MPAs) and the management and monitoring zones within Italian MPAs. In the studied cases, the <em>MedSens</em> index responds well to the local pressures documented by previous investigations.</p> <p><em>MedSens</em> converts the data collected by trained volunteers into an effective monitoring tool for the Mediterranean subtidal rocky coastal habitats. <em>MedSens</em> can help conservationists and decision-makers identify the main pressures acting in these habitats, as required by the MSFD, supporting them in the implementation of appropriate marine biodiversity conservation measures and better communicate the results of their actions. By directly involving stakeholders, this approach increases public awareness and the acceptability of management decisions, enabling more participatory conservation tactics.</p> <p> </p> <p><strong>References</strong></p> <p>Cerrano C, Milanese M, Ponti M (2017) Diving for science - science for diving: Volunteer scuba divers support science and conservation in the Mediterranean Sea. Aquat Conserv 27:303–323 <a href="https://doi.org/10.1002/aqc.2663">https://doi.org/10.1002/aqc.2663</a><br> Turicchia E, Cerrano C, Ghetta M, Abbiati M, Ponti M (2021) MedSens index: The bridge between marine citizen science and coastal management. Ecol Indic 122:107296 <a href="https://doi.org/10.1016/j.ecolind.2020.107296">https://doi.org/10.1016/j.ecolind.2020.107296</a></p>
SDF format of Crystallography Open Database - April 2023
<p>This is a dump & transform to SDF of the crystallography open database that I computed & published in the context of a blog post. You can use that as alternative to extract angle, dihedral or distance statistics from freely & openly accessible crystal structures. </p>
The ROADMAP Final Event, 26 April 2023
<p>On the 25th and 26th of April, we were grateful to organise the ROADMAP final conference at the University Foundation in Brussels. On the 25th of April, before the last conference, an informal network cocktail and dinner were organised at the final event location (University Foundation Brussels). Travelling or local stakeholders were invited for a casual get-together in which discussions and networking were facilitated.<br> <br> On the 26th, the final event took place with presentations from project partners, a round table discussion with policymakers and a lively conversation with our stakeholder advisory board. It was a very inspiring and interactive day.<br> <br> The video recording and aftermovie from the event (26th of April) is available here: https://www.youtube.com/playlist?list=PLW5PYxzlSCfzzdqn2n6-eCxfkGhRAT6Qy</p> <p> </p>
Scraped tweets about women in STEM from April 2022 to May 2023
<p>The data comprises one csv file named tweets. It has 168,677 tweets scraped with the help of snscrape spanning April 2022 to May 2023. Each entry contains metadata regarding the tweet and it's author. The tweets are curated to be representative of discourse regarding women in STEM. The search queries used while scraping are "womeninSTEM", "womeninTech", etc.</p> <p> </p>
Physical oceanography and meteorological data from the W1M3A observatory, Ligurian Sea (North Western Mediterranean) July 2021 - April 2022
<p>Time series data of physical oceanography (salinity, temperature) and meteorology (atmospheric pressure, wind speed and direction, air temperature and humidity, shortwave radiation, longwave radiation and rain) collected from July 2021 to April 2022 by observatory W1M3A at 1h interval. The file contains tabular data (tab delimited) with the following columns: Day; Month; Year; UTC Hour; Minute ; Longitude [deg]; Latitude [deg]; Atmospheric Pressure [hPa]; Wind speed [m/s]; Wind direction [deg]; Air Temperature [°C]; Relative air humidity [%]; Short wave Radiation [W/m2]; Long wave radiation [W/m2]; Rainfall [mm/h]; Sea temperature @ 6 m [°C]; Sea temperature @ 20 m [°C]; Sea temperature @ 36 m [°C]; Salinity @ 6 m [psu]; Salinity @ 20 m [psu], Salinity @ 36 m [psu].</p>
Chlorophyll data from experiments testing for nitrogen, phosphorus, and thiamine limitation of phytoplankton in 39 Ohio lakes of varying trophic status during the growing seasons (April – October) of 2008–2009
Although nitrogen and phosphorus deficiency of algal blooms have been the focus of substantial attention, organic nutrients can limit algal growth in aquatic systems. Growing evidence indicates thiamine (vitamin B1) can influence the community of primary producers in marine systems, but comparatively little is known about the effect of thiamine on freshwater algal productivity. We conducted 106 nutrient deficiency experiments with water from 39 Ohio lakes of varying trophic status during the growing seasons (April – October) of 2008–2009. Specifically, we tested the response of phytoplankton biomass (as chlorophyll a, chl-a) relative to controls to added nitrogen (N), phosphorus (P), thiamine (Th), or combinations of N+P and N+P+Th in integrated surface water collected from the inflow and outflow of each lake. The data presented here show the average chl-a of two replicate samples of each treatment (control, N, P, Th, N+P, N+P+Th), ratio of treatment/control response, and growth response ratio as ln(treatment chl-a/control chl-a). Each entry also includes lake surface water pH at time of collection and the initial chl-a concentration at time of experiment start.
Leaf litter, soil, and periphyton gene expression along freshwater to marine gradients in Everglades National Park (FCE LTER), Florida, USA, January 2021 and April 2021
We collected leaf litter, periphyton, and soil along freshwater to marine gradients at SRS-2, SRS-4, SRS-6, TS/PH-2, TS/Ph-3, TS/Ph-7a, and TS/Ph-10. Samples were collected in January and April of 2021 to understand how microbial communities respond to and influence the breakdown of organic matter along freshwater to marine transects. Data collection for this project is complete. For each site and litter pair we collected a subset of 2-3 g wet mass of litter, a grab sample of soil, and a grab sample of periphyton for each site. All subsamples were preserved at -20°C until extraction, which took place up to a year after initial collection. Samples were sent to Novogene (Novogene Co. Ltd., Beijing, China) for the total RNA extraction followed by metatranscriptome sequencing. We selected n = 12 genes/gene families encoding for focal enzymes to investigate which are important to the breakdown of organic matter: Dioxygenases (associated with aerobic respiration), Sulfatases (associated with the release of sulfates from complex molecules), sulfite reductases (associated with sulfite reduction), methyl coenzyme M reductase and formylmethanofuran (associated with methanogenesis), nitrite reductases (associated with nitrite reduction), cellobiosidase, glucosidase, and xylosidase (associated with cellulose breakdown), phenol oxidase (associated with lignin breakdown), acid phosphatase (associated with phosphate acquisition in acidic environments), and alkaline phosphatase (associated with phosphate acquisition in basic environments). For each gene/family of interest, we searched all annotated transcripts for all entries corresponding to that gene/family and combined all values for a total expression. We selected n = 6 monophyletic microbial functional groups, representing sulfate reducers, sulfate oxidizers, methane oxidizers, methanogens, nitrite oxidizers, and ammonia oxidizers associated with sulfate and methane cycling. We filtered all annotated transcripts for all specie
Movement Metrics for Common Snook and Atlantic Tarpon in the Coastal Everglades, Florida, USA, July 2016 to April 2021
This dataset contains acoustic telemetry derived residency and movement metrics for Common Snook (Centropomus undecimalis) and Atlantic Tarpon (Megalops atlanticus) tracked in two neighboring estuarine systems in the coastal Florida Everglades by the Coastal Everglades Lakes Acoustic Array. Data were summarized at the quarter-season level (early dry, late dry, early wet, late wet) across multiple years (2016–2021), resulting in 326 records and 15 variables. Each record includes metadata on species identity, year, system, and season, as well as individual-level residency time statistics (minimum, maximum, mean, variance), number of lakes visited, and proportional system use. The dataset provides a standardized summary of spatial and temporal variation in Snook and Tarpon habitat use, suitable for investigating seasonal residency and patterns of movement behavior. Data collection for this package is complete.
Marsh water table height, logging data from the Railroad site on the Parker River for April-December 2006.
Measurements of water table height in the Parker River marsh located downstream of the railroad bridge. Measurements were taken every 10 minutes at each logger along a transect of water level loggers running perpendicular to the Parker River bank at the railroad site, MAR-PR-Wtable-RR, for April - December 2006.
Marsh water table height, logging data from the Typha site on the upper Parker River for April-December 2006.
Measurements of water table height in the upper Parker River Typha sp. marsh. Measurements were taken every 10 minutes at each logger along a transect of water level loggers running perpendicular to the Parker River bank at the Typha site, MAR-PR-Wtable-T, for April - December 2006.
Marsh water table height, logging data from the Typha marsh site on the upper Parker River for April-November 2007.
Measurements of water table height in the upper Parker River Typha sp. marsh. Measurements were taken every 5 minutes at each logger along a transect of water level loggers running perpendicular to the Parker River bank at the Typha site, MAR-PR-Wtable-T, for April - November 2007.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.