Peck, J.E. & P. Muir.
1999. Commercial “moss”
harvesting: estimating the size of
the resource and accumulation rates. Report
to the Eugene District Bureau of Land Management, Eugene, OR.
To
address the growing need for inventory estimates for the special forest product
of epiphytic moss, we implemented a rapid inventory method, developed in a
companion project, in 70 >50 year old upland and riparian forest plots
below 915 m in central western Oregon. These plots were stratified by land
classification and occurred in matrix, AMA, and LSR forest on the Eugene
District, BLM, and within an AMA on the Sweet Home R.D., Willamette National
Forest. Site and stand
characteristics were measured at each plot, as well as whole-plot level
estimates of the number of trees and shrubs, of the number bearing harvestable
moss mats, and of the number of harvestable mats on those trees and shrubs. All commercially harvestable moss was then harvested using
methods commonly employed by commercial harvesters. Data from these plots were used to refine regression models
derived in the companion project to predict plot-level harvestable moss biomass
and the presence of harvestable moss. These
“indices of harvestability” allow rapid estimation of harvestable moss
biomass for forest plots in the study region. To estimate reaccumulation rates, the volume and species
composition of variably sized harvestable moss mats were recorded on 10-20 vine
maple stems in the 13 plots that had sufficient harvestable quantities of moss.
This document represents the final report for the project to implement
the index, estimate accumulation rates, and discuss variation in these epiphyte
communities. This document also
includes: a
discussion of the site characteristics conducive to the development of
harvestable moss biomass, written instructions for repeating these procedures, a
methods manual and datasheets, maps of the sampled sites, lists of the epiphytes
found in the harvestable moss mats, and electronic spreadsheets with all site,
biomass, and species data.