Ecosystem process models at multiple scales for mapping tropical forest productivity

生物群落 生态系统 森林生态学 环境科学 温带森林 温带雨林 温带气候 生产力 生态系统模型 时间尺度 气候变化 植被(病理学) 森林动态 生态学 医学 生物 宏观经济学 病理 经济
作者
Joanne Nightingale,Stuart Phinn,Alex Held
出处
期刊:Progress in Physical Geography [SAGE]
卷期号:28 (2): 241-281 被引量:54
标识
DOI:10.1191/0309133304pp411ra
摘要

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.
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