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Modeling for Integrating Science and Management...

by Virginia H Dale, Keith L Kline
Publication Type
Book Chapter
Publication Date
Page Numbers
209 to 237
Publisher Name
Cambridge University Press
Publisher Location
Cambridge, Maryland, United States of America

Modeling relationships between land-management practices and resulting changes in carbon, nitrogen, albedo, and other factors is complex. Even so, such modeling can be used to integrate scientific knowledge and provide a bridge between scientific understanding and policy. Yet, too often decision makers have a poor understanding of the underlying models and thus may misinterpret the implications. More often, decision makers diminish model results as fictitious, for they do not recognize the validity or extent of the underlying science. Decision makers should understand that the modeling process (1) involves formalizing hypotheses concerning relationships among components of human, biophysical, and ecological systems and (2) fosters exploration of implications of those hypotheses. To be most helpful for decision making, developing a model requires documentation of the model components and implications including all assumptions, input and output variables, and methods used to calibrate and validate the model as well as to identify sensitivities and uncertainties. There is no one modeling approach that meets the diverse needs of decision makers regarding land and carbon issues. As with all scientific explorations, new learning typically results in improved understanding, new questions, and revised hypotheses about the way the system works. Decision makers need to realize that models cannot provide specific predictions any more than models are to be believed. Instead, modeling enhances understanding of a system by requiring a formal statement of what is known and not known. The advantages and cautionary principles involved in using models for decision making are discussed. Because land change is a local or regional process and many questions about the effect of these changes are at the global scale, there are still gaps in modeling land change and its effects. The chapter concludes with opportunities to improve modeling of land change and the carbon cycle so that the scientific understanding and information on these issues is presented in a way that is more useful to decision makers.