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首页> 外文期刊>Philosophical Transactions of the Royal Society of London, Series B. Biological Sciences >The impact of Cenozoic cooling on assemblage diversity in planktonic foraminifera
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The impact of Cenozoic cooling on assemblage diversity in planktonic foraminifera

机译:新生代冷却对浮游有孔虫组合多样性的影响

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摘要

The Cenozoic planktonic foraminifera (PF) (calcareous zooplankton) have arguably the most detailed fossil record of any group. The quality of this record allows models of environmental controls on macroecology, developed for Recent assemblages, to be tested on intervals with profoundly different climatic conditions. These analyses shed light on the role of long-term global cooling in establishing the modem latitudinal diversity gradient (LDG) one of the most powerful generalizations in biogeography and macroecology. Here, we test the transferability of environment -diversity models developed for modern PF assemblages to the Eocene epoch (approx. 56-34 Ma), a time of pronounced global warmth. Environmental variables from global climate models are combined with Recent environment diversity models to predict Eocene richness gradients, which are then compared with observed patterns. The results indicate the modern LDG lower richness towards the poles developed through the Eocene. Three possible causes are suggested for the mismatch between statistical model predictions and data in the Early Eocene: the environmental estimates are inaccurate, the statistical model misses a relevant variable, or the intercorrelations among facets of diversity e.g. richness, evenness, functional diversity have changed over geological time. By the Late Eocene, environment diversity relationships were much more similar to those found today.
机译:新生代的浮游有孔虫(PF)(浮游动物浮游动物)可以说是所有族群中最详细的化石记录。该记录的质量使得可以针对具有明显不同的气候条件的时间间隔测试针对最近的组合开发的宏观生态环境控制模型。这些分析揭示了长期的全球冷却在建立现代纬度多样性梯度(LDG)中的作用,该梯度是生物地理学和宏观生态学最有力的概括之一。在这里,我们测试了为现代PF组件开发的环境多样性模型到始新世时期(大约56-34 Ma)的可转移性,这个时期是全球温暖的时期。来自全球气候模型的环境变量与最近的环境多样性模型相结合,以预测始新世的丰富度梯度,然后将其与观测到的模式进行比较。结果表明,现代LDG对通过始新世发育的两极的富集度较低。对于早期始新世统计模型预测与数据之间的不匹配,提出了三种可能的原因:环境估计不准确,统计模型缺少相关变量或多样性方面的相互关系,例如丰富性,均匀性,功能多样性随着地质时间的变化而变化。到晚始新世,环境多样性的关系与今天发现的更加相似。

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