The past five decades have witnessed a rapid growth of computer models for simulating ecosystem functions and dynamics. This has been fueled by the availability of remote sensing data, computation capability, and cross-disciplinary knowledge. These models contain many submodules for simulating different processes and forcing mechanisms, albeit it has become challenging to truly understand the details due to their complexity. Most ecosystem models, fortunately, are rooted in a few core biophysical foundations, such as the ...
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The past five decades have witnessed a rapid growth of computer models for simulating ecosystem functions and dynamics. This has been fueled by the availability of remote sensing data, computation capability, and cross-disciplinary knowledge. These models contain many submodules for simulating different processes and forcing mechanisms, albeit it has become challenging to truly understand the details due to their complexity. Most ecosystem models, fortunately, are rooted in a few core biophysical foundations, such as the widely recognized Farquhar model, Ball-Berry-Leuning and Medlyn family models, Penman-Monteith equation, Priestley-Taylor model, and Michaelis-Menten kinetics. This text includes tools such as spreadsheet (or Python codes) templates for modeling exercises with different input parameters as online materials, which include datasets, parameter estimation, and real-world applications. Users can also apply their own datasets. The materials included in this volume serve as effective tools for users to understand model behaviors and uses with specified conditions.
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