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Temperature-dependent evolutionary speed shapes the evolution of biodiversity patterns across tetrapod radiations
Systematic Biology ( IF 6.1 ) Pub Date : 2022-07-09 , DOI: 10.1093/sysbio/syac048
A Skeels 1, 2 , W Bach 1, 2 , O Hagen 1, 2, 3 , W Jetz 4, 5 , L Pellissier 1, 2
Affiliation  

Biodiversity varies predictably with environmental energy around the globe, but the underlaying mechanisms remain incompletely understood. The evolutionary speed hypothesis predicts that environmental kinetic energy shapes variation in speciation rates through temperature- or life history-dependent rates of evolution. To test whether variation in evolutionary speed can explain the relationship between energy and biodiversity in birds, mammals, amphibians, and reptiles, we simulated diversification over 65 million years of geological and climatic change with a spatially explicit eco-evolutionary simulation model. We modelled four distinct evolutionary scenarios in which speciation-completion rates were dependent on temperature (M1), life history (M2), temperature and life history (M3), or were independent of temperature and life-history (M0). To assess the agreement between simulated and empirical data, we performed model selection by fitting supervised machine learning models to multidimensional biodiversity patterns. We show that a model with temperature-dependent rates of speciation (M1) consistently had the strongest support. In contrast to statistical inferences, which showed no general relationships between temperature and speciation rates in tetrapods, we demonstrate how process-based modelling can disentangle the causes behind empirical biodiversity patterns. Our study highlights how environmental energy has played a fundamental role in the evolution of biodiversity over deep time.

中文翻译:

温度依赖性的进化速度塑造了四足动物辐射的生物多样性模式的进化

生物多样性随全球环境能源的变化而变化,但其背后的机制仍不完全清楚。进化速度假说预测,环境动能通过依赖于温度或生命史的进化速率来塑造物种形成速率的变化。为了测试进化速度的变化是否可以解释鸟类、哺乳动物、两栖动物和爬行动物的能量和生物多样性之间的关系,我们使用空间明确的生态进化模拟模型模拟了 6500 万年的地质和气候变化。我们模拟了四种不同的进化场景,其中物种形成完成率取决于温度(M1)、生命史(M2)、温度和生命史(M3),或者独立于温度和生命史(M0)。为了评估模拟数据和经验数据之间的一致性,我们通过将监督机器学习模型拟合到多维生物多样性模式来进行模型选择。我们表明,具有与温度相关的物种形成速率 (M1) 的模型始终获得最强的支持。统计推论表明四足动物的温度和物种形成率之间没有一般关系,与此相反,我们证明了基于过程的建模如何能够理清经验生物多样性模式背后的原因。我们的研究强调了环境能源如何在生物多样性的长期演化中发挥着基础性作用。我们表明,具有与温度相关的物种形成速率 (M1) 的模型始终获得最强的支持。统计推论表明四足动物的温度和物种形成率之间没有一般关系,与此相反,我们证明了基于过程的建模如何能够理清经验生物多样性模式背后的原因。我们的研究强调了环境能源如何在生物多样性的长期演化中发挥着基础性作用。我们表明,具有与温度相关的物种形成速率 (M1) 的模型始终获得最强的支持。统计推论表明四足动物的温度和物种形成率之间没有一般关系,与此相反,我们证明了基于过程的建模如何能够理清经验生物多样性模式背后的原因。我们的研究强调了环境能源如何在生物多样性的长期演化中发挥着基础性作用。
更新日期:2022-07-09
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