Machine learning ecological networks.
Machine learning ecological networks.
复制标题
机器学习生态网络。
DOI：
10.1126/science.add7563
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
O'Gorman EJ
中科院分区：
文献类型：
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作者：
O'Gorman EJ
也许并不令人惊讶的是，顶级捕食者，如鲸鱼、鲨鱼、豹和老虎，也往往是最稀有的物种。这在很大程度上是因为食物链中每一级的能量传递都不完美，这使得这些食肉动物比草食动物、有害动物或杂食动物更容易挨饿。它们的生存还取决于它们有一个广阔的栖息地，可以四处游荡，寻找维持种群生存所需的配偶和资源。这些脆弱性使它们特别容易受到人类活动的影响，例如栖息地丧失或因其战利品地位而成为猎人的目标。在本期的第1008页，Frickeet等人采用了一种基于网络的方法来确定在过去的13万年里，人类是如何扰乱顶端捕食者和其他哺乳动物动物的。
It is perhaps unsurprising that apex predators, such as whales, sharks, leopards, and tigers, also tend to be the rarest species . This is largely because of the imperfect transfer of energy through each level in a food chain , which makes these carnivores more susceptible to starvation than herbivores, detritivores, or omnivores. Their survival also depends on having a large home range for them to roam far and wide to find the mates and resources needed to sustain their populations . These vulnerabilities make them particularly susceptible to human activities, such as habitat loss or being targeted by hunters for their trophy status. On page 1008 of this issue, Frickeet al.adopt a network-based approach to establish how humans have disrupted apex predators and other mammalian fauna over the past 130,000 years.