Morphologic variation of two key biostratigraphical proteaceous-like pollen taxa across the Cretaceous–Paleogene boundary in northern South America
收藏Taylor & Francis Group2020-12-22 更新2026-04-16 收录
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https://tandf.figshare.com/articles/dataset/Morphologic_variation_of_two_key_biostratigraphical_proteaceous-like_pollen_taxa_across_the_Cretaceous_Paleogene_boundary_in_northern_South_America/7937609
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<i>Echitriporites trianguliformis</i> and <i>E</i>. <i>suescae</i> comb. nov. are two species of proteaceous-like triaperturate pollen that have been widely reported in several sedimentary sequences from northern South America, especially in Colombia and Venezuela. Despite their biostratigraphic significance and because of their morphological similarity, distinction between the two species has been difficult, leading to a biased understanding of their chronostratigraphic ranges. In this study, we compare 75 pollen grains spanning the Maastrichtian–Danian time interval through traditional and geometric morphometrics, and a newly proposed Procrustes-based method (index of pollen curvature). Traditional assessments show subtle variation between specimens; however, geometric morphometrics and the curvature index allow quantifying morphological differences in the degree of concavity-convexity through time. Therefore, geometric morphometrics and curvature index results enable us to constrain the stratigraphic ranges of both taxa. We suggest a coetaneous range for <i>E. trianguliformis</i> and <i>E. suescae</i> comb. nov. during the Late Cretaceous, but the presence of only <i>E. trianguliformis</i> after the Cretaceous–Paleogene boundary event. In addition, we propose a threshold value of 1.5 µm for the curvature index as a tool for distinguishing between these two taxa. We conclude that the combination of geometric morphometrics and the curvature index provides a powerful tool to distinguish between morphological closely-related pollen taxa that are difficult to distinguish through both light microscope visual comparisons and statistical analysis of morphometric measurements.
创建时间:
2019-04-02



