TreeSpec: Quantifying the functional role of canopy structural and chemical traits for productivity across experimental tree diversity gradients using a hyperspectral imaging system

林冠结构和生理的量化对于了解树种对森林生态系统功能的影响是不可或缺的，但森林树冠的高度和复杂性给采样带来了挑战。到目前为止，从鸟瞰角度衡量植物特征的下一代冠层研究工具，如配备高光谱成像的近冠层无人机(UAV)，主要集中在作物单一栽培上。很少有研究应用这些工具来研究更多样化的混交物或森林树冠。因此，我们建议通过测试基于无人机的遥感方法来测量驱动森林生产力的关键特征，并检查它们与实验社区树木物种多样性的关系，以解决这一知识差距。最近的分析表明，森林生产力在很大程度上取决于两个关键的冠层特征：1)叶面积指数(LAI)，描述光捕获；2)冠层叶氮(%N)，描述生物化学碳固定。总而言之，这些特征可能在广泛的时间和空间尺度上将碳通量和森林冠层属性机械地联系在一起。然而，需要对这些关系在其他区域和不同物种池中的普遍性进行测试。聚焦于世界上运行时间最长的两个树木多样性实验，我们将收集和比较从地面和空气中观测到的叶面积指数和%N，并测试它们与生产力的关系。邻近物种和功能组成对树冠形状、LAI和%N相对于单一栽培的影响将使用最先进的无人机成像系统以高分辨率进行检测。这将允许对与建筑互补性和生产力相关的种内性状变异进行新的研究。因此，我们的项目将实现两个主要目标：开发测量关键冠层特征的新方法，以及评估它们在多样性-生产力关系中的潜在作用。

Quantifying canopy structure and physiology is integral to understanding tree species influences on forest ecosystem function, but the height and complexity of forest canopies makes sampling challenging. To date, next generation tools for canopy research that measure plant traits from a birds-eye-view perspective, such as near-canopy Unmanned Aerial Vehicles (UAVs) equipped with hyperspectral imaging, have predominantly focused on crop monocultures. Few, if any studies have applied these tools to examine more diverse mixtures or forest canopies. Therefore, we propose to address this knowledge gap by testing UAV-based remote sensing methods for the measurement of key traits driving forest productivity and examining their relationship to tree species diversity in experimental communities. Recent analyses suggest forest productivity largely depends on two key canopy traits: 1) leaf area index (LAI), which describes light capture, and, 2) canopy leaf nitrogen (%N), which describes biochemical carbon fixation. Together, these traits may mechanistically link carbon fluxes and forest canopy attributes at broad temporal and spatial scales. However, tests of the generality of these relationships in other regions and for different species pools are needed. Focusing on two of the longest-running tree diversity experiments in the world, we will collect and compare observations of LAI and %N from the ground and the air and test their relationship with productivity. Effects of neighbourhood species and functional composition on crown shapes, LAI and %N relative to monoculture will be detected at high resolution using a state of the art UAV-imaging system. This will allow for novel studies of intraspecific trait variation in relation to architectural complementarity and productivity. Our project will thus accomplish two main goals: the development of novel methods of measuring key canopy traits, and the assessment of their potential role in diversity-productivity relationships.