Forest processes and global environmental change: Predicting the effects of individual and multiple stressors. Aber, J.; Neilson, R. P.; McNulty, S.; Lenihan, J. M.; Bachelet, D.; Drapek, R. J..
Bioscience:
2001
Notes
Global change involves the simultaneous and rapid alteration of several key environmental parameters that control the dynamics of forests. We cannot predict with certainty, through direct experimentation, what the responses of forests to global change will be, because we cannot carry out the multisite, multifactorial experiments required for doing so. The physical extent, complexity, and expense of even single-factor experiments at the scale of the whole ecosystem challenge our abilities, although several such experiments have been successfully undertaken (e.g., DeLucia et al. 1999, Wright and Rasmussen 1998). To inform policy decisions, however, the scientific community can offer an interdisciplinary synthesis of existing information. When this synthesis takes the form of a computer model, quantitative predictions can be made that integrate what has been learned from single-factor experiments. The success of such an approach depends on the quality and completeness of the information base and on the rigor of the modeling effort formation. At this time, the major mechanism for determining the degree of uncertainty in predictions is through comparison of results from runs of different models using identical input parameters.