RoL:FELS:RAISE: Design principles of evolved transportation networks in leaf veins

许多生物系统包含运输资源的空间网络。例子包括树枝和动物的循环系统。这些网络的形式千差万别。有些只是分支，而另一些则形成循环。有些有多个层次结构，而另一些则没有。这种变化可能反映了解决各种环境和结构挑战的进化解决方案。该项目将研究工厂中的关键网络功能，包括运输效率、抗破坏能力和机械强度。很少有理论将网络形式与这些函数联系起来，或者预测这些函数之间的权衡。此外，由于收集数据和描述网络结构的困难，很少有网络能够完全表征其结构或功能。更好地理解网络架构背后的规则，将有助于深入了解各种有机形式的进化。在这项研究中确定的原则有一天可以指导人工网络的工程，如太阳能电池或合成器官，可以造福社会。该项目还将通过全面的指导计划支持本科研究人员的职业发展，该计划旨在纳入代表性不足的少数民族学生。本项目将利用叶脉网络作为模型进行实证系统研究。叶片在植物的碳获取和水分流失中发挥着重要作用，通过其脉网络介导资源运输过程。这些网络具有高度的形式和功能多样性，易于表型和功能表征。该项目将1)量化来自温带森林、沙漠和低地/山地热带森林的500种物种的系统发育网络结构；2)确定网络结构与功能/成本之间的联系；3)基于多尺度网络统计开发和测试这些网络功能/成本的理论；4)确定网络结构的宏观进化驱动因素。网络功能将在现场用生态生理学方法进行测量。机器学习方法将用于从图像中提取网络架构。该项目还将支持一名博士后研究员和两名研究生的跨学科培训，他们将获得国际实地考察和合作经验。该奖项反映了美国国家科学基金会的法定使命，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。

Many biological systems contain spatial networks that transport resources. Examples include the branches of trees and the circulatory systems of animals. These networks vary widely in their form. Some only branch, while others form loops. Some have multiple levels of hierarchy, while others do not. This variation may reflect evolved solutions for solving diverse environmental and structural challenges. This project will study key network functions in plants, including transport efficiency, resistance to damage, and mechanical strength. There is little theory linking network form to these functions, or for predicting tradeoffs among these functions. Moreover, very few networks have been fully characterized for structure or function due to the difficulty of collecting the data and describing network architecture. Better understanding the rules underlying network architecture will provide insights into the evolution of diverse organismal forms. The principles identified in this research could one day guide the engineering of artificial networks such as solar cells or synthetic organs that could benefit society. The project will also support career development undergraduate researchers via a comprehensive mentoring program aimed at inclusion of underrepresented minority students.This project will use leaf venation networks are a model empirical system. Leaves are central to plant performance via their roles in carbon gain and water loss, processes mediated by resource transport through their venation networks. These networks have high diversity of form and function and are tractable to phenotyping and functional characterization. This project will 1) quantify network architecture in a phylogenetically broad set of 500 species from temperate forests, desert, and lowland/montane tropical forests, 2) determine how network architecture and functions/costs are linked, 3) develop and test theories for these functions/costs of networks based on multi-scale network statistics, and 4) identify macro-evolutionary drivers of network architecture. Network functionality will be measured in the field with ecophysiology methods. Machine learning methods will be used to extract network architecture from images. The project also will support interdisciplinary training for one postdoctoral researcher and two graduate students, who will gain international fieldwork and collaboration experience.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.