Incorporating the effects of interspecific competition and vegetation management treatments in diameter distribution models for Douglas-fir saplings

Abstract

A parameter recovery procedure for the Weibull distribution function, based on diameter percentiles, was modified to incorporate the effects of interfering vegetation in young Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco var. menziesii) plantations. The applicability of the system was tested by using data from sites in the Coast Ranges of Oregon and Washington and in the Siskiyou Mountains of southwestern Oregon. Four percentiles (0, 25th, 50th, 95th) of the cumulative probability distribution were predicted as functions of quadratic mean diameter and age. In the Siskiyou study, cover and total vegetation control affected quadratic mean diameter and all four percentiles; intensity of the vegetation treatments affected the 0 and 25th percentiles, and the interaction between intensity and timing of treatment affected quadratic mean diameter. In the Coast Ranges study, only quadratic mean diameter was affected by cover of woody vegetation, while quadratic mean diameter and the 25th percentile were significantly affected by total vegetation control. The predicted distributions showed decreasing variance with increasing cover, particularly in the Siskiyou Mountains. In the Coast Ranges study, the coefficient of variation increased with increasing cover, indicating that the variance of stem diameters was affected by average size. On xeric sites in the Siskiyou Mountains, high diameter variability in plots with total vegetation control suggests that interspecific competition may inhibit the expression of microsite variation.

The effect of moose browsing on the height structure of Scots pine saplings in a mixed stand

“…Instead, the effect of browsing on pine and competing broadleaves was most significant in the middle of the distribution. Knowe et al (1992) incorporated the effect of weed control into a diameter distribution model. They found that vegetation management and treatment intensity affected relatively low percentiles (D 0 and D 25 ) but not the median (D 50 ) and less the higher percentiles (D 95 ).…”

“…However, the character of browsing and vegetation management differ as well as character of height and diameter. In contrast to annual effect (Knowe et al, 1992), we could model a long-term effect only. Thus, our results are relevant for the given stage of stands, age of 17 years and mean height of 4 m.…”

A Stand-Class Growth and Yield Model for Mexico’s Northern Temperate, Mixed and Multiaged Forests

“…Nanag [50] noted that the maximum likelihood, percentile, and moment procedures of parameter estimation produce compatible results. Other investigators recommended the percentile technique because of the ease with which it can be used to estimate parameters [51,52].…”

Methods and applications for improving parameter prediction models for stand structures in Finland

“…In addition, it enables prediction and simulation of the future yields and the target stand states for management objectives, such as cutting regimes (Hyink and Moser 1983, McTague and Bailey 1987, Bowling et al 1989, Franklin et al 2002, Newton et al 2005. Furthermore, the effect of genetic improvement, management activities (e.g., vegetation control), or disturbances (e.g., moose browsing) on stand structure can be described through changes in diameter or height distribution (see Knowe et al 1992, Siipilehto and Heikkilä 2004, Smith 2007, Weng et al 2010. The diameter distribution of living trees is also a relevant basis for characterising stand diversity (e.g., Buongiorno et al 1994, Staudhammer and LeMay 2001, Pommerening 2002).…”