A spatangoid echinoid assemblage from the Gutingkeng Formation (Early Pleistocene) of Taiwan and its paleoenvironmental and geological implications

被引:0
作者
Hsu, Chia-Hsin [1 ]
Lin, Jih-Pai [1 ]
Lin, Chien-Hsiang [2 ]
机构
[1] Natl Taiwan Univ, Dept Geosci, Taipei, Taiwan
[2] Acad Sinica, Biodivers Res Ctr, Taipei, Taiwan
关键词
Echinodermata; Echinoidea; Quaternary biostratigraphy; Paleoenvironment; Orogeny; EARLY MIOCENE; SEA-URCHIN; SARDINIA; PALEOECOLOGY; ENVIRONMENTS; FOSSIL; SHELF; TOOL;
D O I
10.1016/j.geobios.2024.09.003
中图分类号
Q91 [古生物学];
学科分类号
0709 ; 070903 ;
摘要
Heart urchins (Echinoidea: Spatangoida) collectively represent a highly diverse group of echinoids with abundant global fossil and extant records. Despite their wide distribution, the preservation challenges associated with their delicate and thin tests have led to limited comprehensive studies of this fossil group in Taiwan. Here, we report a new spatangoid echinoid assemblage from the Early Pleistocene part of the Gutingkeng Formation. Despite the inherent fragility and pronounced deformations in the studied specimens, the preserved key diagnostic characteristics (pore pairs in ambulacrum III and oral plating) indicate most of the fossil echinoids belong to genera Schizaster and Brissopsis. Moreover, based on detailed taphonomic and functional morphological examination, the paleoenvironment of the assemblage is interpreted as a low-energy, fine-grained soft substrate in a deeper shallow-water setting. Furthermore, this assemblage shares a high similarity with Assemblage 3 at the S'Archittu-Cajaragas section in the Miocene of Sardinia, supporting the notion that echinoids are excellent paleoenvironmental indicators, as similar echinoid faunas can be found across continents when environmental conditions are similar. On the other hand, the temporal and geographical distribution of Schizaster-rich echinoid assemblages in Taiwan may be correlated with the Cenozoic orogeny history of Taiwan. (c) 2024 Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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页码:9 / 23
页数:15
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