MSA: Resolving structural diversity controls on ecosystem function along a volume gradient across NEON domains

生物多样性通常被认为是以存在的不同类型生物的数量来衡量的。从这一角度来看，研究表明，生物多样性是决定生态系统特征的一个重要因素，如稳定性和功能，以及不同生态系统维持包括人类在内的地球上所有生命的多种方式。这项研究将从一个非常不同的角度-通过空间结构-审查生物多样性。该项目将研究不同类型的植物在不同生态系统（如草地，灌木丛和森林）内和之间相互排列和分层的三维模式。这种结构多样性影响着植物如何获得资源，反过来又控制着生态系统的健康和功能。结构多样性可能受到植被最大体积的限制，因此森林可能比灌木丛和草地具有更高的结构多样性和功能。研究将使用来自国家生态观测网络（氖）空中观测平台的遥感数据来测试这些生态系统类型内部和之间的结构多样性如何变化。这将得到使用低飞无人机收集的新的更精细规模数据的补充。这些分析将用于为利用遥感测量各生态系统的结构多样性建立新的理论基础。该项目所产生的理解可能导致在地方到区域范围内监测和管理生态系统的新方法。该项目还将努力通过弥合生态学家数据科学教育的差距，增加STEM中代表性不足的群体的保留。新的宏观系统生物学为重点的课程和研究经验，将培养学生在美国最大的西班牙裔美国人servingInstitute.The项目的目标是揭示结构多样性影响生态系统功能和生物多样性的程度类似沿着植物体积梯度在宏观系统scales，以及是否有独特的结构属性的生态系统类型，管理连接结构多样性和功能的机制。具体目标是：（1）检验结构多样性与功能和生物多样性沿着植物体积梯度在不同空间尺度上是否存在相同的关系;（2）检验环境因子在结构多样性-功能和-生物多样性关系的空间格局中的相对重要性。该项目将利用氖数据产生的能量，并将其与一种新的激光雷达无人机数据产品集成在次大陆范围内。这种综合方法特别需要测量草地和灌木地的结构多样性。该项目还将培养多样化的本科生和研究生，并将支持两名早期职业科学家的发展。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Biological diversity is commonly thought of and measured in terms of the number of different types of organisms that are present. Using this perspective, studies have established that biological diversity is an important factor determining ecosystem characteristics such as stability and function, and the many ways that different ecosystems sustain all life on Earth, including humans. This study will examine biological diversity from a very different perspective - by spatial structure. The project will examine the three-dimensional patterns by which different types of plants are arranged and layered in relationship to one another within and between different ecosystems such as grasslands, shrublands, and forests. This structural diversity impacts how plants obtain resources which, in turn, controls the health and functioning of ecosystems. Structural diversity may be limited by the maximum volume of vegetation, so forests may have higher structural diversity and functioning than shrublands and grasslands. Research will use remote sensing data from the National Ecological Observatory Network's (NEON's) Airborne Observatory Platform to test how structural diversity varies within and between these ecosystem types. This will be complimented by new, finer-scale data collected using lower-flying drones. The analyses will be used to develop a new theoretical basis for using remote sensing to measure structural diversity across ecosystems. The understanding generated by this project could lead to a new method for monitoring and managing ecosystems at local to regional scales. The project will also work toward increasing the retention of underrepresented groups in STEM by bridging a gap in data science education for ecologists. New macrosystems biology-focused curriculum and research experiences will train students at the USA’s largest Hispanic American-Serving Institution.The goal of this project is to uncover the degree to which structural diversity influences ecosystem function and biodiversity similarly along a plant volume gradient at macrosystem scales, and whether there are unique structural attributes of ecosystem types that govern the mechanisms linking structural diversity and function. Specific objectives are to: (1) test if the same relationships occur between structural diversity with function and biodiversity along a plant volume gradient across spatial scales, and (2) test the relative importance of environmental factors mediating the spatial patterns of structural diversity-function and -biodiversity relationships. The project will harness the power created by NEON data and integrate it with a new LiDAR drone data product across a sub-continental scale. This combined approach is especially needed for measuring structural diversity in grasslands and shrublands. The project will also train diverse undergraduate and graduate students and will support the development of two early-career scientists.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.