Scaling Predicted Pine Forest Hydrology and Productivity Across the SouthernUnited States. (Chapter 9)

摘要

The objective of this chapter is to examine how the aggregation of input datainfluences the predictive capabilities of forest process models across a changing spatial or temporal resolution. We examine the influence of data aggregation on multiple-scale forest process model development, use, and validation, using PnET-IIS, a physiologically-based model for predicting forest hydrology and productivity at the stand, ecosystem, and regional scales. Overall model structure and data requirements are outlined and model use and limitations at three spatial scales are discussed.