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Verifiability of genus-level classification under quantification and parsimony theories: a case study of follicucullid radiolarians

Published online by Cambridge University Press:  05 August 2020

Yifan Xiao
Affiliation:
State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan430074, China. E-mail: [email protected], [email protected]
Noritoshi Suzuki
Affiliation:
Department of Earth Science, Graduate School of Science, Tohoku University, Sendai980-8578, Japan. E-mail: [email protected]
Weihong He
Affiliation:
State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan430074, China. E-mail: [email protected], [email protected]
Michael J. Benton
Affiliation:
School of Earth Sciences, University of Bristol, BristolBS8 1RJ, U.K. E-mail: [email protected]
Tinglu Yang
Affiliation:
School of Earth Sciences, East China University of Technology, Nanchang330013, China. E-mail: [email protected]
Chenyang Cai
Affiliation:
State Key Laboratory of Palaeobiology and Stratigraphy, Nanjing Institute of Geology and Palaeontology, and Center for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Nanjing210008, China. E-mail: [email protected]

Abstract

The classical taxonomy of fossil invertebrates is based on subjective judgments of morphology, which can cause confusion, because there are no codified standards for the classification of genera. Here, we explore the validity of the genus taxonomy of 75 species and morphospecies of the Follicucullidae, a late Paleozoic family of radiolarians, using a new method, Hayashi's quantification theory II (HQT-II), a general multivariate statistical method for categorical datasets relevant to discriminant analysis. We identify a scheme of 10 genera rather than the currently accepted 3 genera (Follicucullus, Ishigaconus, and Parafollicucullus). As HQT-II cannot incorporate stratigraphic data, a phylogenetic tree of Follicucullidae was reconstructed for 38 species using maximum parsimony. Six lineages emerged, roughly in concordance with the results of HQT-II. Combined with parsimony ancestral state reconstruction, the ancestral group of this family is Haplodiacanthus. Five other groups were discriminated, the Parafollicucullus, Curvalbaillella, Pseudoalbaillella, Longtanella, and FollicucullusCariver lineages. The morphological evolution of these lineages comprises a minimum essential list of eight states of four traits. HQT-II is a novel discriminant analytical multivariate method that may be of value in other taxonomic problems of paleobiology.

Type
Articles
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of The Paleontological Society

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Footnotes

Data available from the Dryad Digital Repository:https://doi.org/10.5061/dryad.547d7wm5r

References

Literature Cited

Aitchison, J. C., Suzuki, N., Caridroit, M., Danelian, T., and Noble, P.. 2017. Paleozoic radiolarian biostratigraphy. Geodiversitas 39:503531.10.5252/g2017n3a5CrossRefGoogle Scholar
Bapst, D. W. 2012. paleotree: an R package for paleontological and phylogenetic analyses of evolution. Methods in Ecology and Evolution 3:803807.CrossRefGoogle Scholar
Caridroit, M., and De Wever, P.. 1986. Some Late Permian radiolarians from pelitic rocks of the Tatsuno Formation (Hyogo Prefecture), southwest Japan. Marine Micropaleontology 11:5590.10.1016/0377-8398(86)90005-8CrossRefGoogle Scholar
Caridroit, M., Danelian, T., O'Dogherty, L., Cuvelier, J., Aitchison, J. C., Pouille, L., Noble, P., Dumitrica, P., Suzuki, N., Kuwahara, K., Maletz, J., and Feng, Q. L.. 2017. An illustrated catalogue and revised classification of Paleozoic radiolarian genera. Geodiversitas 39:363417.CrossRefGoogle Scholar
Clausen, S. E. 1998. Applied correspondence analysis. An introduction. Sage, London.CrossRefGoogle Scholar
Decelle, J., Suzuki, N., Mahé, F., de Vargas, C., and Not, F.. 2012. Molecular phylogeny and morphological evolution of the Acantharia (Radiolaria). Protist 163:435450.CrossRefGoogle Scholar
De Wever, P., Dumitrica, P., Caulet, J. P., Nigrini, C., and Caridroit, M.. 2001. Radiolarians in the sedimentary record. Gordon & Breach, Amsterdam.Google Scholar
Dong, W. Q., Zhou, G. Y., and Xia, L. X.. 1979. Quantitative theory and its application. Jilin People's Publishing House, China. [In Chinese.]Google Scholar
Goloboff, P. A., and Catalano, S. A.. 2016. TNT version 1.5, including a full implementation of phylogenetic morphometrics. Cladistics 32:221238.CrossRefGoogle Scholar
Hayashi, C. 1950. On the quantification of qualitative data from the mathematico-statistical point of view (an approach for applying this method to the parole prediction. Annals of the Institute of Statistical Mathematics 3:3547.CrossRefGoogle Scholar
Hayashi, C. 1954. Multidimensional quantification. II. Proceedings of the Japan Academy 30:165169.CrossRefGoogle Scholar
Hayashi, C. 1988. New developments in multidimensional data analysis. Pp. 316in Hayashi, C., ed. Recent development in clustering and data analysis. Academic Press, Boston, Mass.CrossRefGoogle Scholar
Holdsworth, B. K., and Jones, D. L.. 1980. Preliminary radiolarian zonation for late Devonian through Permian time. Geology 8:281285.2.0.CO;2>CrossRefGoogle Scholar
Huang, R. G. 2016. RQDA: R-based qualitative data analysis, R package version 0.2-8. http://rqda.r-forge.r-project.org, accessed 22 June 2020.Google Scholar
Ishiga, H. 1983. Morphological change in the Permian Radiolaria, Pseudoalbaillella scalprata in Japan. Transactions and Proceedings of the Palaeontological Society of Japan 129:18.Google Scholar
Ishiga, H. 1991. Description of a new Follicucullus species from southwest Japan. Memoirs of the Faculty of Science, Shimane University 25:107118.Google Scholar
Ito, T. 2020. Taxonomic re-evaluation of the Permian radiolarian genus Longtanella Sheng and Wang (Follicucullidae, Albaillellaria). Revue de Micropaléontologie 66:100406.CrossRefGoogle Scholar
Ito, T., Feng, Q. L., and Matsuoka, A.. 2015. Taxonomic significance of short forms of middle Permian Pseudoalbaillella Holdsworth and Jones, 1980 (Follicucullidae, Radiolaria). Revue de Micropaléontologie 58:312.CrossRefGoogle Scholar
Ito, T., Feng, Q. L., and Matsuoka, A.. 2016. Possible boundaries between Pseudoalbaillella and Follicucullus (Follicucullidae, Albaillellaria, Radiolaria): an example of morphological information from fossils and its use in taxonomy. Forma 31:710.Google Scholar
Kan, T. 2017. Training for multivariate analysis with examples and exercises on Excel—survival analysis, logistic analysis and time series analysis. Ohm-sha, Tokyo. [In Japanese.]Google Scholar
Kan, T., and Fujikoshi, Y.. 2010. Qualitative method type II—a discriminant analysis for qualitative data. Genndai-Sugakusha, Tokyo. [In Japanese.]Google Scholar
Kumari, S. S. S. 2008. Multicollinearity: estimation and elimination. Journal of Contemporary Research in Management 3:8795.Google Scholar
Li, N., Gu, W., Okada, N., and Levy, J. K.. 2005. The utility of Hayashi's quantification theory for assessment of land surface indices in influence of dust storms: a case study in Inner Mongolia, China. Atmospheric Environment 39:119126.CrossRefGoogle Scholar
Matsuba, T., Ding, C. R., Liu, L., and Chiba, Y.. 1998. The utility of Hayashi's quantification theory type 2 for the rapid assessment of the epidemiological survey in the developing countries—in a case of the vaccine coverage survey in Yunnan Province, China. Journal of Epidemiology 8:2427.CrossRefGoogle ScholarPubMed
Nakagawa, T., and Wakita, K.. 2020. Morphological insights from extremely well-preserved Parafollicucullus (Radiolaria, Order Albaillellaria) from the probable Roadian (Guadalupian, middle Permian) manganese nodule in the Nishiki Group of the Akiyoshi Belt, southwest Japan. Paleontological Research 24:161167.CrossRefGoogle Scholar
Nakamura, Y., Imai, I., Yamaguchi, A., Tuji, A., and Suzuki, N.. 2015. Molecular phylogeny of the widely distributed marine protists, Phaeodaria (Rhizaria, Cercozoa). Protist 166:363373.CrossRefGoogle Scholar
Nakamura, N., Sandin, M. M., Suzuki, N., Tuji, A., and Not, F.. 2020. Phylogenetic revision of the Order Entactinaria—Paleozoic relict Radiolaria (Rhizaria, SAR). Protists 127:125712.CrossRefGoogle Scholar
Nestell, G. P., and Nestell, M. K.. 2020. Roadian (earliest Guadalupian, Middle Permian) radiolarians from the Guadalupe Mountains, west Texas, USA. Part I: Albaillellaria and Entactinaria. Micropaleontology 66:150.Google Scholar
Noble, P., Aitchison, J. C., Danelian, T., Dumitrica, P., Maletz, J., Suzuki, N., Cuvelier, J., Caridroit, M., and O'Dogherty, L.. 2017. Taxonomy of Paleozoic radiolarian genera. Geodiversitas 39:419502.CrossRefGoogle Scholar
Ormiston, A., and Babcock, L.. 1979. Follicucullus, new radiolarian genus from the Guadalupian (Permian) Lamar Limestone of the Delaware Basin. Journal of Paleontology 53:328334.Google Scholar
Paradis, E., and Schliep, K.. 2019. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35:526528.CrossRefGoogle ScholarPubMed
Sandin, M. M., Pillet, L., Biard, T., Poirier, C., Bigeard, E., Romac, S., Suzuki, N., and Not, F.. 2019. Time calibrated morpho-molecular classification of Nassellaria (Radiolaria). Protist 170:187208.CrossRefGoogle Scholar
Stevens, S. S. 1946. On the theory of scales of measurement. Science 103:877–680.CrossRefGoogle ScholarPubMed
Takasawa, T., Tanaka, M., Gonda, Y., and Kawabe, H.. 2010. Characteristic analysis of landslides and slope failure in the Imo River Basin induced by the mid Niigata Earthquake using GIS. Pp. 632641 in Interpraevent 2010 Symposium Proceedings. International Research Society, Taipei.Google Scholar
Tanaka, Y. 1979. Review of the methods of quantification. Environmental Health Perspectives 32:113123.CrossRefGoogle ScholarPubMed
Wang, Y. J., Luo, H., and Yang, Q.. 2012. Late Paleozoic radiolarians in the Qinfang area, southeast Guangxi. China University Science Technical Press, Hefei.Google Scholar
Xiao, Y. F., Suzuki, N., and He, W. H.. 2018. Low-latitudinal standard Permian radiolarian biostratigraphy for multiple purposes with unitary association, graphic correlation, and Bayesian inference methods. Earth-Science Reviews 179:168206.CrossRefGoogle Scholar
Zhang, L., Ito, T., Feng, Q. L., Caridroit, M., and Danelian, T.. 2014. Phylogenetic model of Follicucullus-lineages (Albaillellaria, Radiolaria) based on high resolution biostratigraphy of the Permian Bancheng Formation, Guangxi, South China. Journal of Micropalaentology 33:179192.CrossRefGoogle Scholar
Zhang, L., Feng, Q. L., and He, W. H.. 2018. Permian radiolarian biostratigraphy. Geological Society of London Special Publication 450:143163.CrossRefGoogle Scholar