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

许多生物系统都包含着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。有的只形成分支，有的则形成环状。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演变解决方案。该项目将研究植物中的关键网络功能，包括运输效率、抗损伤能力和机械强度。几乎没有理论将网络形式与这些功能联系起来，或者预测这些功能之间的权衡。此外，由于收集数据和描述网络架构的困难，很少有网络的结构或功能得到充分表征。 更好地理解网络结构的基本规则将有助于深入了解不同生物形式的进化。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，这些都可以造福社会。该项目还将通过一个全面的指导计划支持职业发展本科研究人员，旨在纳入代表性不足的少数民族学生。叶片通过其在碳获得和水分损失中的作用而对植物性能起着核心作用，这些过程通过其脉序网络由资源运输介导。这些网络具有高度多样性的形式和功能，并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个物种的网络架构，2）确定网络架构和功能/成本如何联系，3）开发和测试基于多尺度网络统计的网络功能/成本理论，以及4）识别网络架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。

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.