CAREER: Integrating causal evolutionary processes into phylogenetic comparative biology

对“行动中的进化”的研究揭示了很多关于进化变化的原因，包括为什么它有时会失败。然而，这些原因在几百万年的时间尺度上-主要与生物多样性的进化和维持有关-也是造成灭绝和适应的原因，这一点并不总是显而易见的。随着全球变化速度的加快，了解物种如何以及为何适应并生存，或未能适应并死亡至关重要。该项目通过一套新的计算工具和生物学研究和教育资源，在短期内研究的进化原因与现有进化多样性的长期结果之间建立了一座桥梁。新的模型将把野外、遗传和实验研究与整个生命树的性状变化模式结合起来。该研究将把这些模型应用于哺乳动物和鱼类的综合数据集，以更好地了解数百万年时间尺度上性状变化的原因。这项研究还将开发和实施免费提供的课堂资源，专门解决短期和长期进化时间尺度上的规模和因果关系问题-教育下一代公民和科学家应对预测当前全球变化将如何影响生物多样性长期前景的紧迫挑战。最近的争论表明，仅从宏观进化数据可以做出什么样的推论存在很大的局限性。解决这些局限性的一个办法是将我们从实地和实验研究中所知道的关于进化的原因和局限性的知识综合到宏观进化方法中。该项目确定了三个“注射点”，这些信息可以整合到比较模型，以阐明宏观进化的原因。该研究将开发新的模型，将遗传变异，自然选择和种群数据的测量与宏观进化尺度数据相结合。它还将使基于性状功能知识的生物力学模型的集成成为可能。通过将宏观进化模型与微观进化数据如何影响进化过程的知识和数据相结合，这项研究将为研究宏观进化的原因开辟新的途径。这些模型将进一步连接到因果推理领域-通过重新思考统计方法如何表示因果关系，这已经彻底改变了人工智能。最后，研究将通过开发和调查如何在生物课程中从孟德尔遗传学到宏观进化的非直观转变来解决生物学教学中未填补的空白。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Studies of “evolution-in-action” have revealed much about the causes of evolutionary change, including why it sometimes fails. However, it is not always obvious when these causes are also responsible for extinction and adaptation over million-year timescales--the timescale primarily relevant to the evolution and maintenance of biodiversity. With increasing rates of global change, it is vital to understand how and why species either adapt and survive, or fail to adapt and perish. This project builds a bridge between the causes of evolution studied over short timescales and the long-term outcomes evident from existing evolutionary diversity with a new set of computational tools and resources for biology research and education. New models will integrate field, genetic and experimental studies with patterns of trait change from across the tree of life. The research will apply these models to comprehensive datasets in mammals and fishes to better understand the causes of trait change over million-year timescales. The research will also develop and implement freely available classroom resources that specifically address issues of scale and causation over short and long evolutionary timescales--educating the next generation of citizens and scientists to the pressing challenge of predicting how current global change will affect the long-term outlook of biodiversity. Recent controversies suggest strong limits on what inferences can be made from macroevolutionary data alone. One solution to these limitations is to synthesize what we know about the causes and limits of evolution from field and experimental studies into macroevolutionary methods. This project identifies three "injection sites" where such information can be integrated into comparative models to elucidate the causes of macroevolution. The research will develop new models that integrate measurements of genetic variation, natural selection and population data with macroevolutionary scale data. It will also enable integration of biomechanical models based on knowledge of trait functions. By uniting macroevolutionary models with knowledge and data on how microevolutionary data affect the evolutionary process, this research will open new paths for studying the causes of macroevolution. These models will be further connected to the field of causal inference--which has revolutionized artificial intelligence by rethinking how statistical methods represent causation. Finally, the research will address unfilled gaps in biology pedagogy by developing and investigating how to make the non-intuitive shift from Mendelian genetics to macroevolution in biology curricula. This will be accomplished by developing and implementing novel, software-based Open Education resources across multiple institutions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.