Ecologists are using increasingly complex computer simulations to describe the dynamics of heterogeneous populations, communities, and ecosystems. This trend, facilitated by improved computational power, reflects an increased understanding of the complex interactions among individuals and their environments. Computer simulations allow the explicit mechanistic interactions among individuals to be parameterized directly from field measurements. These simulations give ecologists the ability to explore hypotheses about community and ecosystem dynamics. These models, unfortunately, are impossible to describe in the same concise fashion as simple analytic models. In addition, the complexity of these models may obscure which of the myriad interactions in the simulation are critical to the key predictions of the model.
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| Base-line forest | Frequent disturbance | Large clear-cut | Increased mortality |
Views of several SORTIE forests. Each image is linked to a higher resolution version of the same image.
Finding the relevant interactions in a complex simulation model is a powerful way to explore the model and discover how the interactions among individuals drive the large-scale dynamics. Using model error analysis and experimentation, we analyzed the behavior of a model of forest dynamics (SORTIE) that takes into account individual trees. We also demonstrated the power of three-dimensional (3D) visualizations in illustrating how the key interactions drive this complex model of a forest community.
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Copyright © 1997 by the American Association for the Advancement of Science.
