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Notes: Is Succession in Hardwood Forests a Stationary Markov Process?

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Past research has applied stationary Markov models to three kinds of problems arising in forestry: individual tree level models of forest succession, plot/canopy gap level models of forest succession, and stand level analyses of specific forest management problems. This class of stochastic model rests on two assumptions concerning the probability of the system moving from one state to another. First, the transition probabilities do not change over time--the process is stationary. Second, once the system is found in some specific state, the probabilities for the next transition do not depend on the path taken to get to that state--the Markov property. One plot level model of forest succession indicates that the stationarity assumption is violated. More complex models, Markov or otherwise, are needed to represent adequately the complicated spatial and temporal dynamics of forest succession. Forest Sci. 26:566-570.
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Keywords: Forest succession; stationarity assumption

Document Type: Miscellaneous

Affiliations: Assistant Professor of Forestry, School of Forestry and Environmental Studies, Yale University, 205 Prospect Street, New Haven, CT 06511

Publication date: 1980-12-01

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    Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
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    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

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    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
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