Biophysical Models and Applications in Ecosystem Analysis
by
Jiquan Chen
Book Details
Format
Paperback / Softback
Book Series
Ecosystem Science&Applications
ISBN-10
1611863937
ISBN-13
9781611863932
Publisher
Michigan State University Press
Imprint
Michigan State University Press
Country of Manufacture
US
Country of Publication
GB
Publication Date
Mar 15th, 2021
Print length
172 Pages
Weight
286 grams
Dimensions
22.90 x 15.20 x 2.50 cms
Ksh 6,050.00
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he materials included in this volume serve as effective tools for users to understand model behaviours and uses with specified conditions and in situ applications.
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. After an introduction of biophysical essentials, four chapters present the core algorithms and their behaviors in modeling ecosystem production, respiration, evapotranspiration, and global warming potentials. Each chapter is composed of a brief introduction of the literature, in which model algorithms, their assumptions, and performances are described in detail. Spreadsheet (or Python codes) templates are included in each chapter for modeling exercises with different input parameters as online materials, which include datasets, parameter estimation, and real-world applications (e.g., calculations of global warming potentials). 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 and in situ applications.
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