Tree communities, airborne remote sensing and ecosystem function: new connections through a traits framework applied to a tropical elevation gradient

生态群落的组成与其生态系统功能之间的关系是什么？群落组成的变化如何影响碳和养分循环？生态系统生产力的变化（例如通过施肥）如何影响多样性的变化？在人类对生态系统的直接压力和全球大气变化的间接压力的背景下，这些可能是生态学日最重要的问题。在这里，我们建议收集数据，开发和评估一个框架，以推进这些想法，在热带森林的树木群落组成的背景下，我们利用三个强大的工具，我们的研究团队和项目合作伙伴已经开发：（i）海拔样带的研究地点在安第斯山脉-亚马逊，树木群落组成和动态已详细描述;（ii）最近在同一样带收集的机载高光谱和激光雷达数据，能够以前所未有的细节确定森林结构和化学，以及（iii）利用植物特征提出从群落组成到生态系统功能的机械方法的理论框架。我们将通过以下方式添加到这些数据集：1。进行了广泛的叶材性状收集活动的七个地点沿着这个样带，和2。收集氮和磷循环的数据。然后，我们将开发每个地块的森林冠层的3D模型（基于林木普查和激光雷达数据），以：3。探讨叶片性状与树体水平特征（总初级生产力、木材生产力、地上净初级生产力和养分循环）的关系。从单个树木到整个小区的生态系统特征（生产力，木材生产，养分循环）在开发了将单个树木属性与小区功能相关联的详细框架之后，我们将尝试简化系统，看看生态系统级别的属性是否可以从对群落中特征的平均值和分布的理解中得出。最后，我们将探讨如何以及树级特征可以通过机载高光谱和激光雷达描述，从而探讨是否有可能描述景观水平的生态系统功能在数千公顷的规模。我们已经组建了一支由英国和美国领先的研究人员组成的团队，并有机会对这些重要问题做出重大进展和新颖的贡献。最终，我们寻求获得一个机械的理解森林群落组装和生态系统水平的过程之间的关系。这一目标的实现将代表生态学的一个重大进步，即开发一个理论和经验工具包来实现这一目标。

What is the relationship between the composition of an ecological community and its ecosystem function? How do changes in community composition affect carbon and nutrient cycling? How does a shift in ecosystem productivity (e.g. through fertilization) feed through to changes in diversity? These are perhaps the most important questions in ecology day, in the context of direct human pressure on ecosystems and indirect pressure through global atmospheric change. Here we propose to collect the data and develop and evaluate a framework to advance these ideas, in the context of tree community composition of tropical forests.We take advantage of three powerful tools that our team of investigators and project partners have developed: (i) an elevation transect of study sites in the Andes-Amazon where tree community composition and dynamics have been described in detail; (ii) airborne hyperspectral and lidar data that have recently been collected over this same transect, that enable determination of forest structure and chemistry in unprecedented detail, and (iii) a theoretical framework that utilises plant traits to propose a mechanistic approach to scale from community composition to ecosystem function. We will add to these datasets by: 1. Conducting an extensive leaf and wood traits collection campaign for seven sites along this transect, and2. Collecting data on nitrogen and phosphorus cycling. Then we will develop a 3D model of the forest canopy of each plot (based on forest tree census and lidar data) to:3. Explore the relationship between leaf traits and tree level characteristics (gross primary production, wood production, above-ground net primary production and nutrient cycling)4. Scale from individual trees to the whole plot ecosystem characteristics (productivity, wood production, nutrient cycling)Having developed this detailed framework for relating individual tree properties to plot-level function, we will try to simplify the system to see if ecosystem level properties can be derived from an understanding of the mean value and distribution of traits in a community. Finally, we will explore how well tree-level characteristics can be described by airborne hyperspectra and lidar, and thus explore whether it is possible to describe landscape level ecosystem functioning at the scale of thousands of hectares. We have assembled a team of leading UK and USA researchers, and have an opportunity to make major advances and novel contributions to these important questions. Ultimately, we seek to acquire a mechanistic understanding of the relationship between forest community assembly and ecosystem level processes. Achievement of this goal would represent a major advance in ecology, in developing a both a theoretical and empirical toolkit with which to reach this goal.