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An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems

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Abstract

Computer models are increasingly being used by forest ecologists and managers to simulate long-term forest landscape change. We review models of forest landscape change from an ecological rather than methodological perspective. We developed a classification based on the representation of three ecological criteria: spatial interactions, tree species community dynamics, and ecosystem processes. Spatial interactions are processes that spread across a landscape and depend upon spatial context and landscape configuration. Communities of tree species may change over time or can be defined a priori. Ecosystem process representation may range from no representation to a highly mechanistic, detailed representation. Our classification highlights the implicit assumptions of each model group and helps define the problem set for which each model group is most appropriate. We also provide a brief history of forest landscape simulation models, summarize the current trends in methods, and consider how forest landscape models may evolve and continue to contribute to forest ecology and management. Our classification and review can provide novice modelers with the ecological context for understanding or choosing an appropriate model for their specific hypotheses. In addition, our review clarifies the challenges and opportunities that confront practicing model users and model developers.

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Acknowledgements

Dean Urban and two anonymous reviewers provided an excellent review and contributed significantly to the final product. Numerous other people have provided critical review, including Monica Turner, Stephen Carpenter, and Volker Radeloff.

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Scheller, R.M., Mladenoff, D.J. An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems. Landscape Ecol 22, 491–505 (2007). https://doi.org/10.1007/s10980-006-9048-4

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