Bark Thickness Equations for Mixed-Conifer Forest Type in Klamath and Sierra Nevada Mountains of California
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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
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| Series: | International Journal of Forestry Research |
| Online Access: | http://dx.doi.org/10.1155/2016/1864039 |
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| Summary: | 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. |
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| ISSN: | 1687-9368 1687-9376 |