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

Table 4

Performance of bark thickness (BT) models in the Fire and Fuels Extension for the Forest Vegetation Simulator (FFE-FVS) [11, 12] and Larsen & Hann [13] models for BT in Oregon applied to BT and DBH data for California mixed-conifers. Comparing BT data for Klamath National Forest (KNF), Tahoe National Forest (TNF), Stanislaus-Tuolumne Experimental Forest (STEF), and Sequoia National Forest (SNF) in California against FFE-FVS and Oregon BT model predictions in terms of percent difference between predicted BT and actual BT data calculated as 100 × (predicted-actual)/predicted. Negative percentage indicates underprediction by the FFE-FVS or Oregon models.

Species	FFE-FVS BT models [11, 12]	Oregon BT models [13]
White fir (ABCO)	−47.7%	−49.2%
Incense-cedar (CADE)	−55.2%	−14.4%
Jeffrey pine (PIJE)	−20.1%	—
Sugar pine (PILA)	−0.5%	11.2%
Douglas-fir (PSME)	6.9%	37.2%
Western white pine (PIMO)	−17.3%	—
Lodgepole pine (PICO)	−5.4%	—
Red fir (ABMA)	−53%	—