Characterising forest landscapes using a stationary and a roving tower eddy covariance system: linking point data to landscape-level characterisations of growth and yeild

拟议的工作涉及开发一个森林生长的生态系统级模型，将现有的10个参数的净生态系统生产力模型扩展到景观，将模型的每月生长预测与当地的生物物理条件联系起来。这些条件将通过将温度和叶面积的遥感图像与太阳辐射和土壤含水量的卫星级模拟相结合而得出。 森林生态系统特征描述和NEP模型参数设定将以固定基站和流动塔系统收集的信息为基础。37米高的固定塔将提供长期的基本天气和生态数据。这一信息沿着NEP和气象数据收集的森林网站与一个巡回塔将被用来（1）推导出所需的森林特定的生长参数为不同的森林覆盖，（2）延长2-3周的时间序列的NEP在景观水平上的应用。将非经济伙伴关系的点测量与森林生长联系起来是一种创新;然而，拟议的项目通过将计算应用于适合森林管理规划的空间尺度上的模拟森林景观，将这项工作向前推进了一步。

The proposed work involves the development of a landscape-level model of forest growth by extending an existing 10 parameter net ecosystem productivity (NEP) model to the landscape by linking the model's monthly growth projections to local biophysical conditions. These conditions are to be derived by combining remote sensing-based images of temperature and leaf area with landscape-level simulations of solar radiation and soil water content. Forest ecosystem characterisation and NEP model parameter setting are to be based on information collected by a stationary base station and roving tower system. The 37-m stationary tower will provide long term base weather and ecological data. This information along with NEP and weather data collected at forest sites with a roving tower will be used to (1) derive the required forest-specific growth parameters for different forest cover, and (2) extend 2-3 week-long time series of NEP for application at the landscape level. Linking point-measurements of NEP to forest growth is innovative; however, the proposed project takes this work a step further by applying the calculations to a modelled forest landscape at spatial scales appropriate for forest management planning.