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International Journal of Forestry Research
Volume 2016 (2016), Article ID 1864039, 10 pages
http://dx.doi.org/10.1155/2016/1864039
Research Article

Bark Thickness Equations for Mixed-Conifer Forest Type in Klamath and Sierra Nevada Mountains of California

Department of Forestry and Wildland Resources, Humboldt State University, 1 Harpst St. Arcata, CA 95521, USA

Received 10 July 2016; Revised 4 October 2016; Accepted 1 November 2016

Academic Editor: Mark Finney

Copyright © 2016 Nickolas E. Zeibig-Kichas et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We studied bark thickness in the mixed-conifer forest type throughout California. Sampling included eight conifer species and covered latitude and elevation gradients. The thickness of tree bark at 1.37 m correlated with diameter at breast height (DBH) and varied among species. Trees exhibiting more rapid growth had slightly thinner bark for a given DBH. Variability in bark thickness obscured differences between sample locations. Model predictions for 50 cm DBH trees of each species indicated that bark thickness was ranked Calocedrus decurrens > Pinus jeffreyi > Pinus lambertiana > Abies concolor > Pseudotsuga menziesii > Abies magnifica > Pinus monticola > Pinus contorta. We failed to find reasonable agreement between our bark thickness data and existing bark thickness regressions used in models predicting fire-induced mortality in the mixed-conifer forest type in California. The fire effects software systems generally underpredicted bark thickness for most species, which could lead to an overprediction in fire-caused tree mortality in California. A model for conifers in Oregon predicted that bark was 49% thinner in Abies concolor and 37% thicker in Pseudotsuga menziesii than our samples from across California, suggesting that more data are needed to validate and refine bark thickness equations within existing fire effects models.