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灭绝事件对古生物地理格局的影响已引起关注,近期研究表明奥陶纪末大灭绝事件后多样性显著高于传统认识,而全球该时期腕足动物的古生物地理分布情况尚未见报道。本文基于已发表的和最新的资料及所掌握新数据的整理,建立全球腕足动物志留纪初鲁丹(Rhuddanian)早期(残存期)13个产地72属137个出现信息(occurrence)和鲁丹晚期(复苏早期)26个产地91属272个出现信息的数据集。同时,运用聚类分析(CA)和非度量性多元标度变换(NMDS),对奥陶纪末大灭绝后残存期及复苏早期腕足动物进行定量古生物地理研究,发现残存期及复苏早期腕足动物具有沿纬度分带倾向。对鲁丹早、晚期腕足动物数据的频率分析表明,灭绝前大多数世界性分子(cosmopolitan taxa)在灭绝后收缩其分布范围,甚至局限于一个产地或古板块以躲避灾难,待环境好转,腕足动物多样性增高的同时,更多分子扩散其分布,显示“复苏”的迹象。通过对古生物地理数据频率的分析,文章讨论了6个相似性测度(si milarity measure),并对其适用性与待分析数据结构的关系提出初步认识。建议在相关研究中使用聚类分析的同时辅以其它统计手段(如NMDS),从而使分析结果更加客观可信。
Recent studies have shown that the diversity after the Great Ordovician mass extinctions was significantly higher than that of the traditional understanding. However, the paleogeographical distribution of brachiopods in this period has not been reported yet. Based on the published and updated data and the compilation of new data, this paper established 137 occurrences of 72 genera and 13 occurrences of Rhuddanian in the early (surviving) In late stage (early recovery), there are 26 datasets in 91 genera and 272 appearing information. At the same time, quantitative paleoegeological studies on the remnant period after Ordovician extinction and brachiopods early in recovery were performed by cluster analysis (CA) and non-metric multivariate scale transformation (NMDS). It was found that the remnant period and early brachiopods Has a tendency to band along the latitude. Frequency analysis of early and late Luridan brachiopods showed that most cosmopolitan taxa before extinction contracted their distribution after extinction and were even confined to a place of production or old plateau to avoid catastrophe until the environment improved. As animal diversity increases, more molecules proliferate their distribution, showing signs of “recovery.” Through the analysis of paleontology geography data frequency, the article discusses six similarity measures (si milarity measure), and puts forward the initial understanding of its applicability and the relationship between the data structure to be analyzed. It is suggested that clustering analysis should be used in the relevant research supplemented by other statistical means (such as NMDS), so as to make the analysis more objective and credible.