A finer record of biodiversity We have pressing, human-generated reasons to explore the influence of environmental change on biodiversity. Looking into the past can not only inform our understanding of this relationship but also help us to understand current change. Paleontological records depend on fossil availability and predictive modeling, however, and thus tend to give us a picture with large temporal jumps, millions of years wide. Such a scale makes it difficult to truly understand the action of environmental forces on ecological processes. Enabled by a supercomputer, Fan et al. used machine learning to analyze a large marine Paleozoic dataset, creating a record with time intervals of only ∼26,000 years (see the Perspective by Wagner). This fine-scale resolution revealed new events and important details of previously described patterns. Science, this issue p. 272; see also p. 249 A temporally refined record derived from 11,000 marine fossils elucidates patterns of diversification and extinction events. One great challenge in understanding the history of life is resolving the influence of environmental change on biodiversity. Simulated annealing and genetic algorithms were used to synthesize data from 11,000 marine fossil species, collected from more than 3000 stratigraphic sections, to generate a new Cambrian to Triassic biodiversity curve with an imputed temporal resolution of 26 ± 14.9 thousand years. This increased resolution clarifies the timing of known diversification and extinction events. Comparative analysis suggests that partial pressure of carbon dioxide (Pco2) is the only environmental factor that seems to display a secular pattern similar to that of biodiversity, but this similarity was not confirmed when autocorrelation within that time series was analyzed by detrending. These results demonstrate that fossil data can provide the temporal and taxonomic resolutions necessary to test (paleo)biological hypotheses at a level of detail approaching those of long-term ecological analyses.

中文翻译：

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寒武纪至早三叠世海洋无脊椎动物生物多样性的高分辨率总结

更精细的生物多样性记录 我们有紧迫的、人类产生的理由来探索环境变化对生物多样性的影响。回顾过去不仅可以让我们了解这种关系，还可以帮助我们了解当前的变化。然而，古生物学记录取决于化石的可用性和预测模型，因此往往会为我们提供具有数百万年宽的大时间跳跃的图片。这样的尺度使得我们很难真正理解环境力量对生态过程的作用。由超级计算机启用，Fan 等人。使用机器学习来分析大型海洋古生代数据集，创建了时间间隔仅为 26,000 年的记录（参见 Wagner 的观点）。这种精细分辨率揭示了先前描述的模式的新事件和重要细节。科学，这个问题 p。272; 另见第 249 来自 11,000 块海洋化石的经过时间改进的记录阐明了多样化和灭绝事件的模式。理解生命史的一大挑战是解决环境变化对生物多样性的影响。模拟退火和遗传算法用于合成来自 3000 多个地层剖面的 11,000 种海洋化石物种的数据，以生成新的寒武纪至三叠纪生物多样性曲线，推算时间分辨率为 26 ± 14.9 万年。这种增加的分辨率澄清了已知的多样化和灭绝事件的时间。比较分析表明，二氧化碳分压 (Pco2) 是唯一似乎显示出与生物多样性类似的长期模式的环境因素，但是当通过去趋势分析该时间序列内的自相关时，这种相似性并未得到证实。这些结果表明，化石数据可以提供必要的时间和分类分辨率，以在接近长期生态分析的细节水平上测试（古）生物学假设。