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

一个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？生态系统生产力的转变（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带来的间接压力的背景下，这些可能是生态时代最重要的问题。在此，我们建议在热带森林树木群落组成的背景下，收集数据并开发和评估一个框架来推进这些想法。我们利用了我们的研究团队和项目合作伙伴开发的三个强大工具：(i)安第斯-亚马逊研究地点的海拔样带，其中树木群落组成和动态已被详细描述；（ii）最近在同一样带上收集的航空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成分；（iii）利用植物特性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增加这些数据集：在这片样带的7个地点开展了广泛的树叶和木材特征收集活动；收集氮和磷循环的数据。然后，我们将基于森林树木普查和激光雷达数据，建立每个样地的森林冠层三维模型：3 .探讨叶片性状与树级特征（总初级生产量、木材生产量、地上净初级生产量和养分循环）之间的关系。从单个树木到整个地块的生态系统特征（生产力、木材产量、养分循环）在开发了将单个树木属性与地块级功能联系起来的详细框架之后，我们将尝试简化系统，以了解生态系统级别属性是否可以从对群落特征的平均值和分布的理解中推导出来。最后，我们将探索机载高光谱和激光雷达如何很好地描述树木水平特征，从而探索是否有可能在数千公顷的尺度上描述景观水平的生态系统功能。我们已经组建了一个由英国和美国领先的研究人员组成的团队，并有机会在这些重要问题上取得重大进展和新的贡献。最终，我们寻求获得森林群落组装和生态系统水平过程之间关系的机制理解。这一目标的实现将代表生态学的一个重大进步，在发展一个理论和经验的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.