Reliable predictions of how changing climate and disturbance regimes will affect forest ecosystems are crucial for effective forest management. Current fire and climate research in forest ecosystem and community ecology offers data and methods that can inform such predictions. However, research in these fields occurs at different scales, with disparate goals, methods, and context. Often results are not readily comparable among studies and defy integration. We discuss the strengths and weaknesses of three modeling paradigms: empirical gradient models, mechanistic ecosystem models, and stochastic landscape disturbance models. We then propose a synthetic approach to multi-scale analysis of the effects of climatic change and disturbance on forest ecosystems. Empirical gradient models provide an anchor and spatial template for stand-level forest ecosystem models by quantifying key parameters for individual species and accounting for broad-scale geographic variation among them. Gradient imputation transfers predictions of fine-scale forest composition and structure across geographic space. Mechanistic ecosystem dynamic models predict the responses of biological variables to specific environmental drivers and facilitate understanding of temporal dynamics and disequilibrium. Stochastic landscape dynamics models predict frequency, extent, and severity of broad-scale disturbance. A robust linkage of these three modeling paradigms will facilitate prediction of the effects of altered fire and other disturbance regimes on forest ecosystems at multiple scales and in the context of climatic variability and change. You may order additional copies of this publication by sending your mailing information in label form through one of the following media. Please specify the publication title and series number.
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Executive SummaryThe overall goal of the integrated modeling program described in this document is to obtain fine-scale predictions of ecosystem attributes across large geographical areas and project them over time under changing climate and disturbance regimes.Reliable prediction requires focus on mechanisms and responses and attention to spatial heterogeneity and temporal disequilibria.The fundamental unit of ecological analysis is the organism, and fundamental scales are those at which the organism strongly interacts with critical or limiting resources.A multi-scale approach is thus required, incorporating ecological conditions at the scale of treefall gaps, slope facets, catchments, and watersheds.Gradient analysis of environmental tolerances, ecosystem dynamics modeling, and landscape dynamics simulation modeling all contribute components required to predict the ecological responses of forests to changing climate and disturbanceMany of the sources of uncertainty in gradient modeling can be mitigated by addressing biotic interactions, spatial dependence, and scaling relationships with multi-scale modeling and hierarchical variance partitioning within the driver-response paradigm.Predictive vege...