Gradual Global Environmental Change in the Real World and Step Manipulative Experiments in Laboratory and Field: The Necessity of Inverse Analysis


Ecosystem responses to perturbation generated by a step increase in climatic variables, such as CO2 concentration and temperature as in field manipulative experiments, are different from responses as a result of a gradual increase in climatic variables as in the real world. This chapter discusses how results from manipulative experiments can be analyzed to improve our predictive understanding of ecosystem responses to future gradual climate change. We first describe gradual changes in several global environmental variables and the corresponding manipulative experiments. Then we review a modeling study by Luo and Reynolds (1999) on differential responses of ecosystems to gradual vs. step changes in CO2 concentration. We also review results from several experiments to verify that ecosystem responses to step CO2 increases are different from those to gradual changes. Finally, we introduce a framework of analysis techniques – inverse analysis – that extract information from experimental data toward predictive understanding in ecological research. The inverse analysis fundamentally focuses on data analysis for parameter estimation and evaluation of alternative model structures so as to improve our predictive understanding from both experimental observations and prior knowledge about the ecosystem processes.


Soil Respiration Inverse Analysis Ecosystem Response Manipulative Experiment Global Change Factor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Dr. Miao and three anonymous reviewers for their constructive comments and suggestions that made this chapter much improved. Our work has been supported by grants from the Office of Science (BER), U.S. Department of Energy, grant DE-FG03-99ER62800 DE-FG02-006ER64319, and National Science Foundation (DEB0444518).


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© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Botany and MicrobiologyUniversity of OklahomaNormanUSA

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