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相关概念视频

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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What is Evolutionary History?02:35

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Scientists record evolutionary history by analyzing fossil, morphological, and genetic data. The fossil record documents the history of life on Earth and provides evidence for evolution. However, both fossil and living organisms offer evidence that outlines Earth’s evolutionary history.
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Threats to Biodiversity01:50

Threats to Biodiversity

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There have been five major extinction events throughout geological history, resulting in the elimination of biodiversity, followed by a rebound of species that adapted to the new conditions. In the current geological epoch, the Holocene, there is a sixth extinction event in progress. This mass extinction has been attributed to human activities and is thus provisionally called the Anthropocene. In 2019 the human population reached 7.7 billion people and is projected to comprise 10 billion by...
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相关实验视频

Updated: Jun 26, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
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Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

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深度潜水:通过使用深度学习,通过时间估计全球生物多样性模式.

Rebecca B Cooper1,2, Joseph T Flannery-Sutherland3, Daniele Silvestro4,5,6

  • 1Department of Biology, University of Fribourg, 1700, Fribourg, Switzerland. rebecca.cooper@unifr.ch.

Nature communications
|May 17, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的深度学习方法,以准确估计过去的生物多样性,克服不完整的化石记录的局限性. 该方法提供了可靠的古生物多样性估计,并修订了对重大灭绝事件的评估.

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科学领域:

  • 进化生物学是进化的生物学.
  • 古生物学的古生物学.
  • 计算生物学是一种计算生物学.

背景情况:

  • 估计过去的生物多样性对于进化生物学来说至关重要,但由于化石记录不完整而受到阻碍.
  • 现有的统计方法很难完全纠正空间,时间和分类学抽样偏差.

研究的目的:

  • 开发一种新的方法,通过时间推断全球或区域生物多样性.
  • 将空间,时间和分类学抽样变化纳入古生物多样性估计.
  • 为过去的生物多样性提供更强大,更准确的评估.

主要方法:

  • 利用生物多样性的随机模拟.
  • 开发了一个深度学习模型来推断财富.
  • 纳入空间,时间和分类学采样变化.
  • 使用模拟数据集和经验数据验证了方法.

主要成果:

  • 新方法的性能优于其他方法,特别是在大型空间尺度上.
  • 在各种保护场景中提供了可靠的古生物多样性估计.
  • 对两次海洋大规模灭绝的数量评估进行了修订.
  • 揭示了鼻类动物的快速多样化和普莱斯托时代多样性显著下降.

结论:

  • 开发的方法在估计过去的生物多样性方面取得了重大进展.
  • 提供了对进化模式和灭绝事件的更准确的理解.
  • 适用于各种数据集,增强古生物学研究.