Rd. Yanai et al., WOODY UNDERSTORY RESPONSE TO CHANGES IN OVERSTORY DENSITY - THINNING IN ALLEGHENY HARDWOODS, Forest ecology and management, 102(1), 1998, pp. 45-60
Understanding the effects of silvicultural treatments on understory ve
getation is important in predicting the consequences of such treatment
s, not only on regeneration but also on wildlife habitat, visual quali
ties, and recreation. We sought to develop an empirical model of under
story response that could be generalized to other forest types. We ana
lyzed understory populations of tree species for 15 years following th
inning to different residual relative densities in 50- to 55-year-old
Allegheny hardwoods. The average number of stems 1 ft (0.3 m) tall to
1 in (2.5 cm) dbh increased for 3 to 5 years after thinning and then l
eveled-off or decreased after 10 or 15 years, The greatest density of
understory stems developed at low residual density. In stems 1 to 3 ft
(0.3 to 0.9 m) tall, the densities of shade-tolerant species were unr
esponsive to thinning while the shade-intolerant were most responsive.
The shade-intolerant and -intermediate species increased in importanc
e over time in the more heavily thinned treatments. In the 3 ft (0.9 m
) tall to 1 in (2.5 cm) dbh size class, shade-intolerant and intermedi
ate species were more responsive to thinning than tolerant species, bu
t shade-tolerant species remained more important numerically throughou
t the study. In growth to > 1 in diameter classes was greatest by shad
e-tolerant stems, increased over time, and was enhanced by thinning. W
e used repeated measures analysis of variance to model the number of s
tems in these three size classes and three shade-tolerance classes as
a function of residual relative density at thinning and time since tre
atment. These models explained 0.08 to 0.80 of the variation in stem n
umbers, depending on the size and tolerance class. These descriptions
might be improved by reference to prior conditions of the regeneration
or interfering herbaceous competition, but a model that required this
information would not be capable of predicting responses to future tr
eatments. (C) 1998 Elsevier Science B.V.