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Landscape Ecology

, Volume 27, Issue 8, pp 1091–1108 | Cite as

Mapping large-scale forest dynamics: a geospatial approach

  • Jingjing Liang
Research Article

Abstract

Digital map of forest dynamics is emerging as a useful research and management tool. As a key issue to address in developing digital maps of forest dynamics, spatial autocorrelation has been distinguished into “true” and “false” gradients. Previous ecological models are mostly focused on either “true” or “false” gradient, and little has been studied to simultaneously account for both gradients in a single model. The main objective of this study was to incorporate both gradients of spatial autocorrelation in a deterministic geospatial model to provide improved accuracy and reliability in future digital maps of forest dynamics. The mapping was based on two underlying assumptions—unit homogeneity and intrinsic stationarity. This study shows that when the factors causing the spatial non-stationarity have been accounted for, forest states could become a stationary process. A prototype geospatial model was developed for the Alaska boreal forest to study current and future stockings across the region. With areas of the highest basal area increment rate projected to cluster along the major rivers and the lowest near the four major urban developments in Alaska, it was hypothesized that moisture limitation and inappropriate human interference were the main factors affecting the stocking rates. These results could be of unprecedented value, especially for the majority of Alaska boreal region where little information is available.

Keywords

Growth and yield Matrix model Universal kriging Controlled trend surface Alaska boreal forest 

Notes

Acknowledgments

The author is obligated to Dr. Dave Verbyla and Randy Peterson for their assistance with spatial analysis and mapping. Bonanza Creek species distribution map is kindly provided by Dr. Dave Verbyla. The author also wants to thank Dr. Mo Zhou, Dr. John Yarie, and Dr. Dave Valentine for their helpful comments. This research is supported in part by the Division of Forestry and Natural Resources, West Virginia University, USDA McIntire-Stennis Act Fund ALK-03-12, and the School of Natural Resources and Agricultural Sciences, University of Alaska Fairbanks.

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Davis College of Agriculture, Natural Resources, and DesignWest Virginia UniversityMorgantownUSA

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