Forest Ecology and Management 258 (2009) 2556–2568
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Forest Ecology and Management
journal homepage: www.elsevier.com/locate/foreco
Patterns of plant community structure within and among primary and
second-growth northern hardwood forest stands
Julia I. Burton a,*, Eric K. Zenner b, Lee E. Frelich c, Meredith W. Cornett d
a
Department of Forest and Wildlife Ecology, University of Wisconsin – Madison, 1630 Linden Drive, Madison, WI 53706, United States
School of Forest Resources, The Pennsylvania State University, 305 Forest Resources Building, University Park, PA 16802, United States
c
Department of Forest Resources, University of Minnesota, 115 Green Hall, 1530 Cleveland Avenue North, St. Paul, MN 55108, United States
d
The Nature Conservancy in Minnesota, 394 Lake Avenue South, Duluth, MN 55802, United States
b
A R T I C L E I N F O
A B S T R A C T
Article history:
Received 4 May 2009
Received in revised form 4 August 2009
Accepted 5 September 2009
Forest scientists advocate the use of natural disturbance-based forest management for restoring the
characteristics of old-growth forests to younger second-growth northern hardwood stands. However,
prescriptions rely upon studies that have (1) not spanned the full range of conditions and species
assemblages, and (2) focused primarily on contrasting old-growth and mature second-growth stands at a
single scale. To examine how the legacy of historical logging activities influences forest structure and
function, we compared and contrasted patterns of plant community structure within and among secondgrowth and primary stands on the north shore of Lake Superior in Minnesota, USA — near the current
range limits of the dominant species, sugar maple (Acer saccharum). We expected second-growth stands
to be in younger developmental stages, and structurally less heterogeneous both within and among
stands. Furthermore, we expected those differences to be associated with patterns of plant community
composition and diversity.
Three of the four primary stands and one of the eight second-growth stands were in the old-growth
stage of development. Yellow birch (Betula alleghaniensis) and conifers as a group (Thuja occidentalis,
Picea glauca and Abies balsamea) were more abundant, and yellow birch was more variable, within
primary stands than second-growth stands. The volume and heterogeneity of coarse woody debris in
intermediate decay- and size classes was also greater within and among primary stands relative to
second-growth stands. While mean subplot richness of overstory tree species was greater in primary
stands, mean quadrat richness, and rates of species accumulation for forest herbs as well as total
herbaceous cover, and graminoid cover were greater in second-growth stands. Furthermore, total basal
area (BA), the BA of conifer species, the density of yellow birch trees, understory vegetation and light
transmittance were more variable among second-growth stands. At the multivariate level, primary
stands were distinguished from second-growth stands not by differences in stand structure, but by a
greater abundance of yellow birch and conifer species in the canopy, which was also related to O-horizon
depth and understory plant species composition and structure. Differences in community structure
between primary and second-growth stands may have resulted from the original cutover as well as highgrade logging, which together may have disrupted the mechanisms that maintain populations of
important co-dominant tree species and associated understory plant communities in northern
hardwood stands.
ß 2009 Elsevier B.V. All rights reserved.
Keywords:
Forest structure
Natural disturbance-based forest
management
Old growth
Primary forest
Second-growth forest
Understory vegetation
1. Introduction
The potential degradation of forest ecosystem goods and
services and loss of biodiversity due to extensive logging has
generated an impetus for developing silvicultural systems that
sustain biodiversity and productivity by mimicking patterns of
* Corresponding author. Tel.: +1 608 265 6321; fax: +1 608 262 9922.
E-mail address: jiburton@wisc.edu (J.I. Burton).
0378-1127/$ – see front matter ß 2009 Elsevier B.V. All rights reserved.
doi:10.1016/j.foreco.2009.09.012
natural disturbance, historical landscape and stand structures, and
historical ranges of variation (Attiwill, 1994; Franklin et al., 2002;
Seymour et al., 2002; Drever et al., 2006). For northern hardwood
forests, specific efforts include those that attempt to accelerate
succession in younger second-growth stands by imposing the
structures that characterize historical landscapes and old-growth
stands (Lorimer and Frelich, 1994; Keeton, 2006). However,
previous studies have focused primarily on average conditions
or a single scale and have not included stands near the range limits
of north-temperate tree species; thus, the legacy of historical
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
logging events on the composition, structure and function of
second-growth stands is not fully understood. Because interactions
among structure, composition and variability at multiple scales
may be important for maintaining the resilience of northern
hardwood forest ecosystems, restoration strategies based solely on
average conditions and successional processes may serve only to
reinforce current differences between primary stands that were
never logged and second-growth stands.
Most of the northern hardwood forests in the upper Great Lakes
region regenerated after extensive logging, known as the cutover,
that occurred at the turn of the 20th century (Zon, 1925). Logging
at this time ranged from the selective removal of economically
valuable tree species to heavy partial cuts and clear-cutting
oftentimes followed by repeated uncontrolled slash fires (Stearns,
1997). This series of events in particular reduced the area of
unharvested, primary stands and stands in the old-growth stage of
development in Minnesota to 0.2% and 2% of the pre-EuroAmerican extent, respectively (Frelich, 1995).
While the cutover greatly reduced the extent of old growth on
the landscape, it may have also initiated more persistent changes
in community structure in regenerating second-growth stands. In
northern hardwoods of the upper Great Lakes region, the natural
disturbance regime resulted in a shifting mosaic of stands in
different stages of development dominated by old growth (Frelich
and Lorimer, 1991). Within stands, the volume of coarse woody
debris (CWD), snag basal area (BA), total area in gaps and average
gap size increase in later stages of development (Tyrrell and Crow,
1994; Dahir and Lorimer, 1996). Studies from the Pacific Northwest show that the range of structural variation and structural
heterogeneity indeed increases with stand age (Spies and Franklin,
1988; Zenner, 2004). Furthermore, compared to conventional
systems of forest harvesting, natural disturbances can also lead to
more complex structures and greater residual heterogeneity
(Hanson and Lorimer, 2007).
Heterogeneity of important community attributes can be both
affected by disturbance, and influence the response of forests to
disturbance (Fraterrigo and Rusak, 2008). In northern hardwood
forests, sugar maple trees can form dense layers of advance
regeneration that excludes light-seeded and mid-tolerant tree
species. Periodic moderate-severity disturbances that create large
canopy openings coincident with seedbeds of rotting CWD and tipup mounds may therefore be important for preventing competitive
exclusion by permitting light-seeded tree species such as yellow
birch and conifers in stands to regenerate and ascend to a canopy
position (Connell, 1979; Cornett et al., 1997; Carlton and Bazzaz,
1998; Woods, 2004). Patterns of herbaceous vegetation are also
associated with environmental heterogeneity imposed by canopy
openings (Moore and Vankat, 1986; Roberts and Gilliam, 1995),
coarse woody debris (Scheller and Mladenoff, 2002) and the
composition of the overstory (Beatty, 1984; Mladenoff, 1987;
Canham et al., 1994; Barbier et al., 2008). Herbaceous vegetation
can interact with tree seedlings establishment after a disturbance
to influence micro-successional pathways (George and Bazzaz,
1999). Thus, spatial variability of key compositional and structural
attributes within forest stands can function to maintain populations of some species over time and, ultimately, the diversity of the
system. Changes in community composition and/or a loss of
structural heterogeneity may therefore degrade ecosystem resilience, or the magnitude of disturbance that a system can
experience before it shifts into an alternative state (Holling, 1973).
Previous studies have documented that mature, second-growth
stands contain fewer large trees in the overstory and snags, and
lower coarse woody debris volumes (Goodburn and Lorimer, 1998,
1999; Hale et al., 1999; McGee et al., 1999) than old-growth stands.
These structural differences between old-growth and mature,
second-growth stands are associated with divergent patterns in
2557
light transmittance and understory plant communities, which are
more fine-grained and patchy in old-growth stands (Crow et al.,
2002; Scheller and Mladenoff, 2002). Although Duffy and Meier
(1992) report devastating effects of logging on the richness and
cover of forest herbs in the southern Appalachians, evidence from
the Lake States suggests that timber harvesting may increase
herbaceous species richness and cover due to the immigration of
weedy and non-native species (Metzger and Schultz, 1984;
Scheller and Mladenoff, 2002).
Here we investigate differences in community structure and
heterogeneity between primary forests with a history of natural
disturbance and regeneration, and second-growth forests that
were logged during the cutover and subsequently high-graded in
northeastern Minnesota. We expected second-growth stands to be
in younger developmental stages, and structurally less heterogeneous both within and among stands. Furthermore, we expected
those differences to be associated with patterns of diversity and
plant community composition and structure. By comparing and
contrasting primary and second-growth stands with respect to
structure, species composition and diversity at multiple scales, we
can characterize the persistent effects of natural and anthropogenic disturbance regimes to inform guidelines for managing and
restoring structure and composition to second-growth stands.
2. Study area
Sugar maple-dominated northern hardwood forests are distributed along the ridge tops on the north shore of Lake Superior
within the transition zone between north-temperate and southern-boreal forests. Elevations range from 200 to 700 m and the
topography is gently rolling to steep. Lake Superior moderates the
climate, which is cold-temperate continental, with a mean
growing season length of 104–168 frost-free days (base temperature = 0 8C), mean annual temperature of 4.72 8C, and mean annual
precipitation of 77.50 cm with 150.4 cm of snowfall (1971–2000,
Midwest Regional Climate Center, http://mcc.sws.uiuc.edu).
This study is part of the pre-treatment phase of a larger project
that examines methods of restoring the composition and structure
of primary stands to second-growth stands. Twelve northern
hardwood stands located in Lake County in northeastern
Minnesota were selected on the basis of cover type, logging
history and lack of recent major natural disturbance (Fig. 1,
Table 1). The selected primary and second-growth stands were
composed of a sugar maple-dominated overstory. Less abundant
overstory species included yellow birch, conifers such as northern
white cedar (T. occidentalis), white spruce (P. glauca) and balsam fir
(A. balsamea), and other hardwood species including black ash
(Fraxinus nigra), paper birch (Betula papyrifera), northern red oak
(Quercus rubra) and red maple (Acer rubrum). Four primary stands
were located on state lands designated for the conservation and
preservation as old growth based on the presence of long-lived
species, lack of a recent catastrophic disturbance and little to no
direct human impacts (Rusterholz, 1996). Thus, stands managed
under the old-growth program in Minnesota were not necessarily
in the old-growth phase of development based on structural
threshold definitions (e.g., Frelich and Lorimer, 1991; Frelich and
Reich, 2003). The eight second-growth stands were located on
nearby county land. The greater sample size for second-growth
stands reflects the design of the long-term experiment that
examines the effects of two replicated (n = 4) structure manipulations on community structure and productivity, as well as the
scarcity of primary stands in the study area. None of the stands
were selected based upon the selection of another stand. With the
exception of two primary stands located within George CrosbyManitou State Park (850 m apart), all stands are separated by
distinct physiographic and vegetation features or with a distance of
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
2558
elevations (Table 1). Two of the primary stands were located in
George Crosby-Manitou State Park, which was donated to the State
of Minnesota to be preserved for primitive outdoor recreation. The
other two primary stands are on smaller tracts, also owned and
managed by the State of Minnesota as part of the old-growth
conservation program (Rusterholz, 1996). Because of the lack of
substantial physiographic variation between stands (Fig. 1,
Table 1), primary stands provide a reasonable reference to which
we can compare second-growth stands of logging origin (Frelich
et al., 2005).
3. Methods
3.1. Field sampling
Fig. 1. Locations of primary stands are indicated by circles, second-growth stands
are triangles. Base layer is 30 m digital elevation model with hill shade. Inset shows
study area location (star) within Minnesota (white) and the upper Great Lakes
region.
at least 1 km. The two primary stands in the State Park were
separated by other stages of development and would be
considered different stands in management. Furthermore, distances between stands did exceed reported ranges of spatial
dependence for the variables examined in this study. Therefore we
are comfortable considering the stands independent and not
pseudo-replicates (e.g., Hurlbert, 1984).
Although the details about the specific histories of each secondgrowth stand are unknown, county-managed lands were forfeited
due to tax delinquency after being logged between the late 1890s
and the mid 1920s and burned subsequently in uncontrolled slash
fires (Tikkanen et al., 1995). High-grading was widely criticized
because it resulted in residual stands that were dominated by
poor-quality timber of little merchantable value (Eyre, 1939);
however, it was also promoted specifically in northern hardwood
stands in the Lake States as a means to provide critical lumber
grades for the war effort (Stott, 1943). Furthermore, many county
stands were selectively harvested for high-grade timber repeatedly, and particularly for conifer species and yellow birch (Dan
Spina and Chris Dunham, personal communication).
Land use history, such as logging, is oftentimes related to
physical features such as topography and soil fertility. However, in
this landscape, there do not appear to be any characteristics unique
to primary or second-growth stands. First, both primary and
second-growth sites are distributed on similar soils at comparable
In each of the 12 stands, we established a 120 m 120 m
(1.44 ha) research plot in the spring of 2003. Twenty-five circular
nested subplots for sampling the overstory, mid-story and groundlayer vegetation were established on a 30 m 30 m grid. A 30 m
distance between subplot centers was chosen so the extent of
sampling would exceed reported ranges of spatial dependence, and
allow us to quantify the heterogeneity of important community
attributes (e.g., Scheller and Mladenoff, 2002). Ground-layer
vegetation was sampled twice during the growing season from
mid-May through mid-September, and diffuse light transmittance
(%light) measurements were taken before leaf fall between
September 6 and September 14, 2003.
Overstory vegetation within a 10 m radius from the subplot
centers was sampled in all 25 subplots in each of the 12 stands
(with the exception of one second-growth stand (BH), which had a
limited sample of 22 subplots). We recorded the species, condition
(i.e., live or dead snag), and diameter at 1.37 m (dbh) for all
trees 10 cm dbh. For a sub-sample of 56 trees that were
selected to represent a replicated sample of the range of existing
diameters and species, we measured crown radii in four cardinal
directions to estimate exposed crown area (ECA). ECA was
calculated as the sum of four quarter ellipses for crown radii of
measured trees and estimated for other trees based on regressions
of ECA on dbh (log(ECA) = 0.1446 + 0.1060dbh 0.0006dbh2,
p < 0.001, r2 = 0.70).
Tree saplings and shrubs 1 m tall but <10 cm dbh were tallied
by species within a 2 m radius of subplot centers. Percent cover of
the ground-layer vegetation (<1 m tall) was estimated by species
within a 1 m2 circular quadrat directly once in the spring prior to
the senescence of spring ephemeral species and once in the
summer. The percent cover of leaf litter, rocks, CWD (5 cm
diameter), exposed mineral soil (EMS) and mosses was estimated
Table 1
Developmental stage classes (old growth = OG) and physiographic characteristics of primary and second-growth stands.
Stand by type
Stage
Lat.
Long.
Elev. (m)
Primary
Caribou river (CR)
Egge pond (EP)
Manitou north (MN)
Manitou south (MS)
OG
Mature
OG
OG
47.5082
47.4669
47.4680
47.4603
91.0602
91.2276
91.1137
91.1135
430
553
463
461
Second-growth
Big pine (BP)
Birch cut (BC)
Brush hog (BH)
Cedar finger (CF)
East Egge (EE)
Hill top (HT)
Power line (PL)
Schoolhouse trail (ST)
Mature
OG
Mature
Mature
Mature
Pole
Mature
Pole
47.4771
47.4500
47.4510
47.4553
47.4570
47.4853
47.9378
47.4592
91.1496
91.1885
91.2041
91.2037
91.2130
91.1354
91.2037
91.1977
465
450
479
478
515
489
390
478
Slope (%)
Aspect (8)
Area (ha)
Light (%)
Soil texture
5
4
8
8
131
75
214
350
38.31
71.40
36.06
57.87
3.6
3.1
1.4
1.0
Loamy–very fine
Loamy–very fine
Loamy–coarse loamy
Loamy–coarse loamy
8
6
1
1
1
8
10
2
162
119
157
83
226
273
142
327
40.47
25.60
16.54
16.54
22.05
13.78
19.67
23.62
1.8
No data
11.6
1.9
1.6
No data
No data
2.0
Loamy–coarse loamy
Loamy–very fine
Loamy–very fine
Loamy–very fine
Loamy–very fine
Loamy–coarse loamy
Fine loamy–hemic
Loamy–very fine
Latitude (Lat.) and Longitude (Long.) are given in decimal degrees. Elevation (Elev.), slope and aspect were derived from a 30-m resolution digital elevation model. Light (%)
was measured at 2 m using a Licor LAI 2000 at a subset of plots. Soil texture was derived from a soils map of Minnesota (Cummings and Grigal, 1981).
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
for all quadrats as well. For all CWD 5 cm within the 10 m subplot
radius, we also measured the diameter at each end and the length
in order to estimate volume. Decay classes (DC) were visually
determined based on the presence of foliage, the shape and
integrity of the wood, where: DC1 = recent, DC2 = solid, DC3 = solid-decayed, DC4 = decayed and DC5 = very decayed (Tyrrell and
Crow, 1994). Depth of the organic horizon (O-horizon) was
measured once in the center of each of four quadrants of each
quadrat during the summer sample by piercing the forest floor
with a ruler until encountering mineral soil. To maximize
consistency, all quadrats were sampled by Burton. Additionally,
to measure the weight of the O-horizon, we collected all leaf litter
and non-woody organic matter within a 0.10 m2 frame placed on
the forest floor at a random distance between 1 and 5 m north of
each quadrat. The samples were air-dried until arrival at the lab
where they could be oven-dried at 50 8C to a constant weight
within 1 g.
Diffuse light transmittance (%light) was measured at 1 m and
approximately 2 m above the subplot centers in five secondgrowth stands and all four primary stands using the LAI-2000 plant
canopy analyzer (LI-COR, Lincoln, Nebraska). The LAI-2000
measures the integrated gap fraction at five concentric angles
simultaneously (Welles and Norman, 1991). Open-canopy measurements were taken concurrently from either a nearby clear-cut
or from the middle of a lake in a canoe, depending on which type of
opening was nearest to the plot. Below-canopy measurements
were matched with the closest-in-time above-canopy measurements and %light was calculated using the post-processing
software C2000 (LI-COR, Lincoln, Nebraska). All measurements
were taken either under cloudy or overcast sky conditions, in the
morning before sunrise or at dusk.
3.2. Characterization of community structure
We assigned each stand to one of four developmental stages:
pole, mature, old-growth, and mature-sapling mosaic (Table 1).
The classification system was developed in a set of 70 primary
northern hardwood stands located in Michigan’s Upper Peninsula
(Frelich and Lorimer, 1991). Assignments were based on the
aggregate exposed crown area (ECA) in the pole (10–24.9 cm dbh),
mature (25–44.9 cm dbh), and large (45 cm dbh) size classes
(Helms, 1998). Stands were classified as (1) old growth when 67%
of ECA was occupied by large and mature trees with more crown
area in large than mature trees; (2) mature 67% of ECA was
occupied by large and mature trees with more crown area in
mature than large trees or when 67% ECA was occupied by poles
and mature trees with more crown area in mature trees than poles;
(3) pole when 67% ECA was occupied by poles and mature trees
with more crown area in poles than mature trees; and (4) maturesapling mosaic when a stand did not meet any of the criteria
described above. Stand classifications were derived from aggregated subplot data.
To examine differences in structural attributes among primary
and second-growth stands, we calculated basal area (BA, m2 ha1)
and live tree density (TPH, trees ha1) as well as metrics derived
from the distribution of total ECA including the 5 cm diameter class
with the greatest aggregate ECA (Modal D) and the percentage of
aggregate ECA in large trees (%large, trees 45 cm dbh). Structural
attributes based on the distribution of total ECA among size classes
of trees have been used to distinguish forest developmental stages
more accurately than stem density or quadratic mean diameter,
and may therefore be more useful than conventional metrics for
describing the structure of the live overstory (Lorimer and Frelich,
1998; Goodburn and Lorimer, 1999) and relating forest structure to
other attributes quantitatively. Structural attributes were calculated for each subplot for all species combined. Density (TPH) and
2559
BA were also calculated for statistical comparison of stand types for
sugar maple (SM), yellow birch (YB), conifers and other hardwoods.
CWD volume was calculated using the equation for a frustum of
a cone (Harmon and Sexton, 1996; McGee et al., 1999) and
summed for each decay and size class. Size classes were based on
the diameter at the mid-point of the log. Size classes were
consistent with the diameter classes used for the classification of
overstory trees described above.
The density of saplings and shrubs 1 m tall and <10 cm dbh
was scaled up to a per hectare basis, and percent cover of woody
vegetation <1 m tall was calculated for each of the following
groups: sugar maple, yellow birch, conifers, other hardwoods and
shrubs. To analyze the ground-layer vegetation, we combined
spring and summer data. When species were observed in both
sampling periods, we used the larger cover estimate for analyses.
For herbaceous species, we calculated total cover (all herbaceous
species combined), as well as the cover of the following guilds of
herbs: ferns, fern allies, graminoids (species in the Poaceae,
Cyperaceae and Juncaceae families), spring ephemerals, earlysummer forbs, late-summer forbs and vines. Spring ephemerals (SE
forbs) are defined as forbs that emerge and senesce prior to canopy
closure, early-summer forbs (ES forbs) emerge early in the spring
and persist through canopy closure, reaching peak coverage before
midsummer, and late-summer forbs (LS forbs) reach peak coverage
after midsummer (Givnish, 1987).
To examine patterns of diversity, we calculated mean subplot
species richness (quadrat/subplot richness) and total species
richness per plot (plot richness) for all species and strata combined,
as well as for life forms (i.e., trees, shrubs and herbs) and strata (i.e.,
overstory, mid-story and ground layer) separately. Average
herbaceous species richness for all possible combinations of 1–
25 subplots (m2) for each plot was calculated in PC-ORD (McCune
and Mefford, 1999) for a comparison of species-area curves.
In addition to calculating the averages of the attributes
described above to characterize the average structural and
compositional conditions at the stand scale, we calculated
standard deviation and range of all subplot values for each plot
to quantify within-stand heterogeneity and the range of variation.
These metrics provide a means to measure absolute levels of
variability in the same units as the data that can be compared using
standard univariate statistics (Fraterrigo and Rusak, 2008).
Among-stand (landscape-scale) variability (dispersion) was quantified for the mean, standard deviation and range of each attribute
by calculating the absolute deviations of each stand from the mean
value of its associated group (i.e., primary or second-growth).
3.3. Statistical analysis
We used t-tests to investigate differences in stand averages and
variability measures (i.e., standard deviations and ranges calculated from sub-samples) of compositional and structural community attributes between primary and second-growth stands.
Levene’s test (Levene, 1960) was used to evaluate the assumption
of equal variances (Schultz, 1985), which were pooled when
differences were not statistically significant (a = 0.10). When
variances were not equal, Satterthwaite’s approximation of
standard errors was used for the tests (Zar, 1974). Levene’s test
for equal variances was also used to examine differences in the
dispersion of community attributes among primary and secondary
stands (Fraterrigo and Rusak, 2008). To compare herbaceous
species-area curves between primary and second-growth stands,
we used a mixed effects model. Species richness and area (i.e., the
number of subplots) were log transformed prior to analysis
(Arrhenius, 1921) and species-area relationships were nested in
the random effect (i.e., plot). Because of the limited sample size of
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J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
primary and second-growth stands in this study, statistical tests
were expected to have a low explanatory power and an increased
probability of accepting the null hypothesis when the null
hypothesis is false (type two error). To account for this effect
we chose an a-level of 0.10 for interpreting statistical significance
(Neyman and Pearson, 1933) and interpreted p-values of 0.05–0.10
as suggestive evidence for significant differences. All univariate
analyses were performed in SAS for Windows (Version 9.1, SAS
Institute 2006).
Multivariate similarity between primary and second-growth
stands was compared using two non-metric multi-dimensional
scaling (NMS) ordinations of (1) all compositional and structural
community attributes described above and (2) understory plant
species in PC-ORD (McCune and Mefford, 1999). NMS avoids the
assumption of linear relationships among variables and uses rank
distances, linearizing the relationships between species abundance and environmental variables (McCune and Grace, 2002).
NMS has been shown to perform better than other common
ordination techniques for a range of data structures common to
community data (Minchin, 1987). It is an iterative approach that is
used more frequently today than historically due to increases in
computing power. Structural and compositional attributes were
relativized across plots using a general relativization by column
totals to eliminate differences in variable units, which could have
caused some factors to influence the ordination disproportionately
(McCune and Grace, 2002). Rare species occurring in fewer than
two plots were excluded from the second ordination of understory
species. We interpret axes by examining Pearson correlations
between the main matrix and plot ordination axis scores, and used
a nonparametric test to evaluate multivariate group differences
between primary and second-growth stands (multi-response
permutation procedure, MRPP; Zimmerman et al., 1985). A
correlation of r > 0.58 is significant at an alpha = 0.05, a correlation
of r > 0.50 is significant at an alpha = 0.10; therefore, we do not
report correlations lower than 0.50. Associations between plot axis
scores and %light were examined separately for the subset of plots
for which we did have %light data (Table 1). Both ordinations and
MRPP analysis used the Sørenson measure of similarity (Kruskal,
1964; Mather, 1976).
Finally, differences in the frequency and abundance of
individual herbaceous species between stand types were examined using indicator species analysis (Dufrêne and Legendre, 1997)
in PC-ORD (McCune and Mefford, 1999). Statistical significance of
indicator species was evaluated using 1000 Monte Carlo randomizations (McCune and Grace, 2002).
4. Results
4.1. Overstory composition and structure
Three of the four primary stands were classified as old growth
and the remaining one was mature. Of the eight second-growth
stands, one was classified as old growth, five as mature and two as
pole. Differences between primary and second-growth stands
depended upon the attribute as well as the scale at which it was
examined (Table 3). Within stands, the range of modal diameters
(Modal D) was significantly greater within primary stands than
second-growth stands (71.25 vs. 55.63 cm, p = 0.044). The
standard deviation and range of BA within stands was more
variable among primary stands than second-growth stands
(p = 0.003, Table 4) while average BA (p = 0.087) was more variable
among second-growth stands. No other attribute describing the
structure of the live canopy varied between stand types when
calculated for all species combined. However, average YB BA
(p = 0.047), YB TPH (p = 0.066) and conifer BA (p = 0.015) were all
greater in primary stands (Table 3). Furthermore, the standard
deviations and ranges of YB BA (p = 0.005 and 0.028, respectively)
and YB TPH (p = 0.007 and 0.064, respectively) were greater within
primary stands than second-growth stands. On the other hand,
mean SM BA (p = 0.013), conifer BA (p = 0.032) and the range of YB
TPH (p = 0.086) were more variable among second-growth stands
than primary stands (Table 4).
4.2. Coarse woody debris and snags
The primary and second-growth stands exhibited differences in
the distribution of CWD among decay and size classes. The average
volume of coarse woody debris in DC2 was greater in primary
stands (p = 0.003), and was more variable within primary stands
than second-growth stands for standard deviations (p = 0.028) and
ranges (p = 0.085; Table 3). The volume of CWD in DC5 was more
variable among primary stands than second-growth stands for
stand averages, standard deviations and ranges (p = 0.014, <0.001
and 0.002, respectively; Table 4). However, the range of mature
snags was more variable among second-growth stands (p = 0.044;
Table 4).
4.3. Understory vegetation and abiotic characteristics
The composition and structure of the understory varied
substantially between primary and second-growth stands at the
stand, within-stand and among-stand scales (Tables 3 and 4). At
the stand scale, total herb cover and graminoid cover was greater
in second-growth stands (p = 0.001 and 0.044, respectively;
Table 3). Within stands, graminoid cover was also more heterogeneous within second-growth stands, as shown by greater
standard deviations (p = 0.008) as well as ranges (p = 0.010). The
among-stand variability of understory attributes was generally
lower for primary stands relative to second-growth stands
(Table 4). Average shrub density (p = 0.050), and the mean sapling
densities, standard deviations and ranges were all more variable
among second-growth stands than primary stands for SM
(p = 0.001, <0.001 and 0.024, respectively) and conifers
(p = 0.061, 0.009 and 0.017, respectively). Furthermore, the
average (p = 0.003), standard deviation (p = 0.015) and range of
graminoid cover (p = 0.021), average late-summer forb cover
(p = 0.047), the standard deviation and range of ground-layer
shrub cover (p = 0.034 and 0.007, respectively), and the mean,
standard deviation and range of both spring ephemeral (p = 0.043,
0.038 and 0.063, respectively) and early-summer forb cover
(p = 0.037, 0.021 and 0.013, respectively) were greater among
second-growth stands relative to primary stands.
Few corresponding differences in abiotic quadrat characteristics were observed at any scale, however. While O-horizon depth
was more variable within (p = 0.059 and 0.049, respectively for
standard deviations and ranges) and among (p = 0.057 for means)
primary stands than second-growth stands, variability in the
standard deviation (p = 0.078) and range (p = 0.070) of diffuse light
transmittance (%light) at 2 m was greater among second-growth
stands.
4.4. Diversity
For all taxa and strata combined, subplot richness was higher in
second-growth stands than primary stands containing 2.5 additional species per subplot on average (p = 0.072, Table 2). Except
for cow parsnip (Heracleum lanatum) and hemp nettle (Galeopsis
tetrahit), which were observed once each in a second-growth stand
and a primary stand, respectively, none of the species observed
were exotic or considered weedy or otherwise invasive. Thus, this
difference could be explained by differences in native quadrat
richness for herbaceous species. On average, second-growth
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
2561
Table 2
Subplot and plot scale species richness by guild and strata (SE in parentheses).
Subplot richness
All taxa and strata
Tree species (all strata)
Overstory trees
Tree saplings
Tree seedlings
Shrub species
Herbaceous species
Plot richness
Primary (n = 4)
Second-growth (n = 8)
T
Pr > jtj
Primary (n = 4)
Second-growth (n = 8)
T
Pr > jtj
7.82
2.73
2.50
1.08
1.19
0.86
4.23
10.32
2.37
1.96
1.11
1.43
1.13
6.83
2.07
1.33
2.31
0.37
1.60
0.83
3.13
0.072
0.222
0.047
0.721
0.073
0.427
0.013
39.75
8.75
7.50
2.75
4.50
5.00
26.00
48.75
8.00
6.62
2.88
4.63
7.25
33.50
1.29
0.95
1.37
0.15
0.14
1.36
1.38
0.227
0.366
0.200
0.882
0.891
0.205
0.197
(0.31)
(0.05)
(0.08)
(0.03)
(0.06)
(0.12)
(0.26)
(1.17)
(0.27)
(0.22)
(0.06)
(0.10)
(0.22)
(0.79)
(3.38)
(0.63)
(0.65)
(0.48)
(0.87)
(0.91)
(2.12)
(4.57)
(0.46)
(0.32)
(0.67)
(0.46)
(1.06)
(3.62)
accumulation (F = 51.91, p < 0.0001 for interactions between stand
type and area). Differences in species-area curves became
negligible at greater extents (Fig. 2). In contrast to herbaceous
species, subplot richness of overstory tree species was lower in
second-growth stands (p = 0.047). Yet, tree seedling quadrat
richness was marginally greater in second-growth stands than
primary stands (p = 0.073) (Table 2).
4.5. Multivariate associations between community attributes and
stand origin
Fig. 2. Predicted species-area curves for primary (solid) and second-growth
(dashed) stands. Points are observed means with error bars showing 95% confidence
intervals. For this mixed effects model, the effects of stand type (F = 5.65, p = 0.039)
and log(area) (F = 9715.75, p < 0.0001) and the interaction between them
(F = 51.91, p < 0.0001) were significant. The random effect is not shown.
contained 1.61 times the number of herbaceous species per square
meter in primary stands, a difference of 2.6 species per quadrat on
average (p = 0.013). Furthermore, species-area curves differed
between primary stands and second-growth stands (Fig. 2).
Primary stands contained fewer species, particularly within small
areas, while second-growth stands had a greater rate of species
The final two-dimensional NMS ordination of community
attributes (Table 3) captured 83.9% of the total variation in
structural and compositional characteristics (58.3% of the variation
on axis 1 and 25.6% on axis 2; Fig. 3), had a final stress of 11.56 and
demonstrated greater structure than expected by chance (based on
a Monte Carlo procedure, a = 0.05). Axis 2 corresponds most
strongly to stand type, which is supported by differences in
community structure between the stand types (MRPP; p = 0.024).
Furthermore, MRPP showed that the average multivariate distance
between second-growth stands (0.41) was greater than primary
stands (0.28).
Overstory characteristics indicating a stronger co-dominance of
yellow birch and conifers in the overstory were strongly correlated
with axis 2 and the locations of primary stands (r = 0.81, 0.73, 0.71
and 0.71 for conifer BA, YB TPH, conifer TPH and YB BA,
respectively). Furthermore, the cover of YB seedlings was
positively associated with axis 2 (r = 0.56). In contrast, the cover
of other hardwood seedlings (r = 0.81), spring ephemerals
Fig. 3. Non-metric multi-dimensional scaling ordination of primary and second-growth stands using stand averages of all community attributes (left) and understory species
abundances (right). The main matrix variables structuring the ordinations and the percentage of variation in the data explained are given for each axis. Circles are primary
stands and triangles are second-growth stands. Biplot overlays show the strength and direction of the correlations between community attributes and axis scores. All
correlations with r2 0.50 (left) and r2 0.30 (right) are shown. BA, basal area; TPH, tree ha1; YB, yellow birch; SM, sugar maple; Con., conifer; Other, other hardwood
species; %shrub, %cover of shrubs <1 m tall; O-H, O-horizon; ES, early summer; SE, spring ephemeral; CWD DC5, coarse woody debris in decay class five.
2562
Table 3
Comparison of community attributes between primary and second-growth stands at stand (mean) and within-stand scales (standard deviation and ranges).
Stand scale (mean of subplots)
Primary (n = 4)
Second-growth (n = 8)
Within-stand heterogeneity (standard deviation of subplots)
Range of variation within stands (range of subplots)
Primary (n = 4)
T
Pr > jtj
(2.40)
(3.95)
(1.48)
(37.27)
1.51
1.20
0.58
0.57
0.162
0.257
0.145
0.580
17.20
22.46
9.45
174.43
0.39
0.65
0.705
0.531
Second-growth (n = 8)
T
Pr > jtj
Primary (n = 4)
Pr > jtj
(0.97)
(1.07)
(0.48)
(14.91)
0.74
0.10
0.59
0.15
0.475
0.926
0.588
0.883
71.25
73.16
36.69
676.41
(3.83)
(4.08)
(2.69)
(61.77)
2.25
0.42
0.52
0.27
0.049
0.686
0.614
0.795
10.92 (1.09)
206.96 (34.66)
8.87 (0.49)
188.97 (16.14)
2.22
0.55
0.051
0.597
43.30 (6.00)
859.44 (105.57)
30.84 (2.40)
708.24 (60.08)
2.34
1.35
0.041
0.208
23.87 (3.14)
127.32 (29.06)
11.86 (2.87)
47.75 (12.03)
2.58
2.53
0.028
0.064
0.164
0.335
25.45 (4.71)
230.77 (47.53)
14.51 (4.71)
139.26 (55.44)
1.45
1.06
0.179
0.315
0.67
0.96
0.517
0.361
13.56 (4.66)
143.24 (54.36)
15.93 (2.69)
258.63 (64.07)
0.48
1.16
0.645
0.274
(1.55)
(2.42)
(1.67)
(2.82)
0.75
0.02
1.36
0.47
0.469
0.988
0.203
0.647
55.70
71.62
151.19
167.11
(7.96)
(7.96)
(7.96)
(7.96)
51.73
75.60
135.28
163.13
0.40
0.28
1.25
0.21
0.699
0.787
0.239
0.849
(1401.9)
(214.25)
(196.79)
(136.66)
(1908.60)
0.71
0.47
1.31
0.85
0.88
0.491
0.649
0.228
0.415
0.401
266.00
994.72
994.72
397.89
911.00
(2064.30)
(596.83)
(198.94)
(397.89)
(5473.30)
0.62
0.45
1.20
0.79
0.93
0.413
0.664
0.265
0.449
0.373
1.13
0.93
0.68
0.13
0.64
0.286
0.376
0.512
0.900
0.543
49.70
33.34
33.48
563.41
Sugar maple
BA (m2 ha1)
LTD (trees ha1)
23.01 (0.45)
469.57 (47.46)
24.43 (2.50)
519.69 (48.62)
Yellow birch
BA (m2 ha1)
TPH (trees ha1)
4.65 (1.13)
26.42 (7.19)
1.11 (0.31)
6.60 (1.98)
3.03
2.66
0.047
0.066
7.31 (1.19)
36.78 (7.66)
2.81 (0.67)
13.83 (3.05)
3.59
3.38
0.005
0.007
Conifers
BA (m2 ha1)
TPH (trees ha1)
4.55 (0.47)
48.38 (7.85)
1.90 (0.76)
26.07 (12.82)
2.94
1.16
0.015
0.275
6.44 (1.00)
60.73 (9.43)
3.67 (1.19)
37.59 (15.14)
1.50
1.01
Other hardwoods
BA (m2 ha1)
TPH (trees ha1)
1.27 (0.64)
19.10 (9.65)
2.54 (0.76)
45.49 (18.78)
1.07
0.94
0.310
0.368
3.32 (1.28)
39.23 (16.41)
4.34 (0.87)
71.06 (21.63)
Snag density
Large (trees ha1)
Mature (trees ha1)
Pole (trees ha1)
Total (trees ha1)
11.14
16.55
31.19
58.89
8.28
14.48
35.81
58.57
(1.42)
(1.92)
(2.90)
(3.28)
1.28
0.59
0.92
0.05
0.230
0.568
0.394
0.965
18.21
22.42
35.11
44.80
16.32
22.36
38.48
42.45
(2000.10)
(83.12)
(98.11)
(28.69)
(958.02)
0.76
0.54
1.12
0.93
0.62
0.320
0.598
0.149
0.376
0.551
6488.10
243.21
214.24
79.58
4003.70
Mid-story (stems ha1)
Sugar maple
Yellow birch
Conifers
Other hardwoods
Shrubs
7504.10
79.58
47.75
15.92
2251.39
(4.44)
(5.48)
(0.87)
(39.79)
(1.31)
(3.16)
(4.11)
(7.70)
(704.77)
(45.94)
(9.19)
(15.92)
(784.48)
42.79
25.16
29.98
597.85
9744.20
147.22
206.90
55.70
3167.70
(2.29)
(1.79)
(1.41)
(30.34)
(1.68)
(2.89)
(0.76)
(4.23)
(792.64)
(140.89)
(37.57)
(79.58)
(1168.10)
15.65
22.65
8.57
169.98
7988.50
395.63
477.08
254.03
6524.90
(6.25)
(6.76)
(5.56)
(79.44)
Second-growth (n = 8)
55.63
70.05
33.89
704.42
(5.82)
(11.94)
(11.25)
(12.67)
30538 (5761.90)
1591.50 (876.90)
1890.00 (720.25)
1193.70 (672.55)
28142.00 (8692.60)
Ground-layer woody (%cover)
Sugar maple
42.67 (4.99)
Yellow birch
0.24 (0.08)
Conifers
0.29 (0.24)
Other hardwoods
0.92 (0.39)
Shrubs
3.37 (0.85)
33.62
0.14
1.14
1.96
3.20
(5.33)
(0.05)
(0.64)
(0.45)
(1.04)
1.08
1.15
0.90
1.46
0.11
0.307
0.278
0.390
0.174
0.918
29.63
0.76
1.39
3.37
7.22
(2.00)
(0.26)
(1.21)
(1.31)
(0.88)
24.68
0.50
3.78
3.99
5.76
(2.03)
(0.17)
(2.30)
(0.95)
(1.41)
1.53
0.86
0.70
0.38
0.88
0.157
0.409
0.501
0.713
0.400
91.00
3.50
6.75
16.75
27.75
(4.30)
(1.19)
(6.09)
(6.50)
(1.60)
Ground-layer herbs (%cover)
Ferns
5.80
Fern allies
2.60
Graminoids
0.90
Spring ephemerals
0.14
Early-summer forbs
1.89
Late-summer forbs
1.55
Vines
0.33
Moss
3.80
Total herb cover
24.51
(2.05)
(1.25)
(0.13)
(0.08)
(0.53)
(0.63)
(0.24)
(1.24)
(3.79)
9.64
1.46
2.87
4.38
5.36
5.43
0.43
2.99
48.29
(2.68)
(0.79)
(0.56)
(1.97)
(2.08)
(2.88)
(0.25)
(1.14)
(9.39)
0.93
0.80
3.41
1.49
1.14
1.32
0.25
0.44
2.35
0.373
0.443
0.010
0.168
0.280
0.226
0.806
0.670
0.044
14.59
5.99
1.97
0.30
5.46
5.02
1.29
9.91
26.57
(3.92)
(2.55)
(0.29)
(0.18)
(0.58)
(2.54)
(0.95)
(2.86)
(4.49)
15.10
3.27
4.86
4.48
7.80
9.77
1.39
7.51
27.82
(3.63)
(1.47)
(0.78)
(1.67)
(2.36)
(4.63)
(0.76)
(2.48)
(3.83)
0.09
0.99
3.46
1.72
0.96
0.90
0.08
0.59
0.20
0.923
0.344
0.008
0.115
0.365
0.390
0.942
0.569
0.847
64.50
25.00
8.25
1.00
25.00
24.00
6.25
42.50
97.50
(17.50)
(10.21)
(1.18)
(0.58)
(2.04)
(12.98)
(4.73)
(13.62)
(13.75)
53.00
13.76
19.50
18.13
31.13
33.25
6.50
30.63
102.50
(12.32)
(6.19)
(3.23)
(7.13)
(8.83)
(15.03)
(3.65)
(9.93)
(14.78)
0.54
1.03
3.27
1.66
0.57
0.39
0.04
0.70
0.21
0.602
0.327
0.010
0.129
0.588
0.702
0.968
0.502
0.835
%Cover
Leaf litter
Rock
CWD (>5 cm)
EMS
(3.57)
(0.52)
(1.62)
(1.66)
88.40
1.94
10.91
1.94
(2.02)
(0.49)
(1.38)
(0.86)
0.58
0.55
0.05
0.84
0.578
0.596
0.957
0.422
19.41
4.97
15.74
9.94
(1.73)
(1.51)
(1.73)
(3.64)
14.65
6.09
15.95
5.04
(2.24)
(1.61)
(1.74)
(1.88)
1.38
0.44
0.08
1.34
0.197
0.672
0.939
0.210
73.75
22.50
56.25
45.00
(9.44)
(7.22)
(6.25)
(16.46)
53.75
26.50
61.88
22.00
(8.60)
(7.68)
(7.56)
(8.24)
1.43
0.33
0.48
1.41
0.183
0.749
0.642
0.188
86.22
1.51
10.78
3.34
81.5 (5.47)
2.25 (0.75)
17.13 (10.15)
15.88 (3.58)
23.88 (5.88)
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
T
All tree species
Modal D
%Large
BA (m2 ha1)
TPH (trees ha1)
O-horizon depth (cm)
O-horizon weight (g)
%Light (1 m)
%Light (2 m)
Total CWD
3.09
34.27
1.77
2.28
118.63
(0.73)
(4.91)
(0.54)
(0.63)
(13.96)
1.72
29.91
2.35
3.78
91.93
(0.26)
(2.51)
(0.90)
(1.95)
(9.55)
1.78
0.89
0.52
0.66
1.60
0.155
0.396
0.620
0.531
0.141
1.54
12.18
1.24
1.60
71.85
(0.22)
(0.98)
(0.25)
(0.35)
(12.05)
0.93
11.80
1.85
3.94
63.73
(0.17)
(0.93)
(0.83)
(2.66)
(2.87)
2.13
0.25
0.62
0.87
0.89
0.059
0.804
0.553
0.431
0.393
6.97
50.37
4.95
5.65
280.52
(1.12)
(3.01)
(0.92)
(1.15)
(39.74)
3.90
50.29
7.46
17.76
247.93
(0.72)
(5.32)
(3.56)
(13.07)
(12.27)
2.24
0.14
0.61
0.92
1.02
0.049
0.888
0.561
0.407
0.333
Decay classes
Class 1 (DC1)
Class 2 (DC2)
Class 3 (DC3)
Class 4 (DC4)
Class 5 (DC5)
1.31
26.76
25.88
32.91
31.77
(0.83)
(2.88)
(4.42)
(5.53)
(8.90)
1.55
11.39
20.97
27.01
31.00
(0.66)
(2.33)
(3.40)
(3.84)
(2.49)
0.22
3.95
0.85
0.88
0.08
0.832
0.003
0.413
0.398
0.938
5.11
40.13
28.02
35.44
31.58
(3.24)
(8.44)
(5.04)
(6.54)
(6.80)
3.71
20.01
26.66
32.91
34.99
(1.05)
(3.75)
(4.54)
(4.20)
(1.98)
0.53
2.56
0.18
0.34
0.63
0.610
0.028
0.858
0.743
0.541
24.07
155.12
102.13
136.69
116.04
(15.79)
(42.61)
(14.67)
(21.29)
(24.95)
15.89
85.69
102.42
129.77
132.32
(4.26)
(15.51)
(16.50)
(21.39)
(8.41)
0.50
1.91
0.01
0.20
0.62
0.647
0.085
0.991
0.843
0.572
Size classes
Large (45+ cm)
Mature (25–45 cm)
Pole (10–25 cm)
Small (5–10 cm)
31.91
51.48
32.06
3.18
(10.02)
(4.66)
(3.80)
(0.20)
27.29
37.65
24.31
2.82
(3.84)
(4.43)
(2.50)
(0.45)
0.53
1.94
1.75
1.95
0.609
0.082
0.111
0.597
42.30
40.83
20.62
1.95
(9.50)
(6.54)
(3.06)
(0.22)
47.05
36.60
17.30
1.80
(3.74)
(2.73)
(1.59)
(0.23)
0.57
0.72
1.08
0.42
0.583
0.490
0.307
0.681
142.10
173.19
78.85
7.49
(29.75)
(41.60)
(11.65)
(1.09)
178.51
146.23
66.37
7.12
(16.39)
(11.95)
(6.06)
(0.86)
1.17
0.62
1.06
0.25
0.268
0.572
0.313
0.805
Table 4
Comparison of dispersion of plot means, standard deviations and ranges of community attributes.
Stand-scale dispersion (subplot means)
BA
SM BA
YB TPA
Conifer BA
SM saplings
Conifer saplings
Shrub density
Shrub cover
SE forbs
ES forbs
LS forbs
Graminoids
O-horizon depth
%Light (2 m)
CWD DC5
Mature CWD volume
Mature snag density
Dispersion of heterogeneity (subplot standard deviations)
Dispersion of ranges (ranges of subplots)
Primary stands (n = 4)
Second-growth (n = 8)
T
Pr > jtj
Primary stands (n = 4)
Second-growth (n = 8)
T
Pr > jtj
Primary stands (n = 4)
Second-growth (n = 8)
T
Pr > jtj
1.32
0.76
10.50
0.69
1042.47
15.92
1296.74
1.37
0.14
0.79
0.83
0.19
1.17
1.07
14.29
6.51
4.46
3.16
5.47
4.44
1.86
4875.13
202.92
2314.08
2.28
3.64
4.23
6.27
1.32
0.55
3.11
5.57
10.71
4.18
1.91
3.32
1.51
2.50
4.46
2.11
2.23
1.04
2.48
2.53
2.27
4.15
2.15
1.73
2.96
1.31
0.14
0.087
0.013
0.215
0.032
0.001
0.061
0.050
0.320
0.043
0.037
0.047
0.003
0.057
0.157
0.014
0.219
0.893
2.41
1.70
11.90
1.47
18777.80
55.09
1829.63
1.19
0.30
0.90
3.53
0.42
0.32
0.50
11.74
9.75
4.18
1.16
1.11
7.06
2.85
3161.40
437.30
4380.66
3.30
3.22
5.05
10.32
1.76
0.35
4.26
4.10
6.19
5.46
3.94
1.22
1.55
1.72
13.15
3.52
1.80
1.36
2.55
2.92
1.80
3.02
0.22
2.33
5.62
1.18
0.61
0.003
0.251
0.153
0.117
<0.001
0.009
0.102
0.034
0.038
0.021
0.101
0.015
0.828
0.078
<0.001
0.267
0.558
9.62
8.89
4.72
6.16
3382.04
298.42
7955.45
2.75
1.00
2.50
18.50
1.75
1.72
1.63
42.86
61.83
11.94
6.93
4.71
27.85
10.26
12632.93
1691.02
18670.45
13.63
12.66
19.16
33.81
7.13
1.55
20.91
17.70
22.47
27.85
4.00
1.34
1.90
0.92
2.81
2.87
1.41
3.81
2.200
3.17
1.23
2.84
0.240
2.45
4.21
2.09
2.31
0.003
0.211
0.086
0.380
0.024
0.017
0.190
0.007
0.063
0.013
0.248
0.021
0.814
0.070
0.002
0.063
0.044
(0.42)
(0.12)
(3.86)
(0.25)
(366.69)
(0.01)
(234.29)
(0.32)
(0.03)
(0.27)
(0.42)
(0.07)
(0.27)
(0.13)
(3.33)
(2.75)
(1.84)
(0.87)
(1.42)
(1.06)
(0.30)
(777.81)
(61.18)
(390.89)
(0.59)
(1.41)
(1.33)
(1.64)
(0.39)
(0.15)
(1.17)
(1.32)
(1.80)
(1.10)
(0.24)
(0.47)
(3.38)
(0.52)
(792.60)
(20.00)
(498.63)
(0.55)
(0.03)
(0.26)
(1.51)
(0.15)
(0.12)
(0.19)
(0.58)
(3.32)
(1.58)
(0.19)
(0.25)
(1.48)
(0.50)
(733.10)
(106.81)
(949.29)
(0.66)
(1.14)
(1.39)
(2.50)
(0.41)
(0.10)
(1.60)
(1.23)
(1.42)
(1.26)
(0.29)
(3.11)
(9.19)
(3.08)
(669.74)
(99.47)
(2976.66)
(0.20)
(0)
(1.44)
(7.38)
(0.61)
(0.51)
(0.66)
(3.13)
(21.35)
(3.98)
(0.61)
(1.61)
(5.82)
(2.73)
(3225.01)
(332.05)
(5075.77)
(2.85)
(5.29)
(5.06)
(7.90)
(1.79)
(0.42)
(7.85)
(5.10)
(8.41)
(5.63)
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
Values are means with standard errors in parentheses. Subplot means of all characteristics were included in the first ordination of plots described by community attributes (Fig. 3).
Dispersion values were calculated as the absolute difference between plot attributes and the respective group means, and provide a means to measure and compare among-stand, or landscape-scale variability (Levene, 1960),
standard errors are given in parentheses. Dispersion was examined at the stand (means) and within-stand scales (standard deviations and ranges). Only those community attributes showing suggestive evidence for significant
differences in dispersion between primary and second-growth stands (p < 0.10) at any scale are shown.
2563
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J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
(r = 0.64), SM BA (r = 0.57), conifer seedling cover (r = 0.53),
the density of other hardwood saplings (r = 0.53), percent cover
of leaf litter (r = 0.51) and early-summer forbs (r = 0.51) were
negatively related to axis 2.
Axis 1 contrasted second-growth stands in later stages of
development dominated by sugar maple with those with greater
abundances of other hardwood species; sugar maple BA (r = 0.82),
percent cover of sugar maple seedlings (r = 0.73), the density of
sugar maple saplings (r = 0.73), %large (r = 0.63), total BA (r = 0.59),
Modal D (r = 0.54) and CWD in DC3 (r = 0.52) were positively
related to axis 2 (Fig. 3) while conifer sapling density (r = 0.88),
other hardwood TPH (r = 0.83), late-summer forb cover
(r = 0.80), total herb cover r = 0.77), other hardwood BA
(r = 0.76), YB sapling density (r = 0.74), shrub cover
(r = 0.74) and density (r = 0.73), conifer TPH (r = 0.72),
graminoid cover (r = 0.59), conifer BA (r = 0.56), ferns and fern
allies (r = 0.53 and 0.51, respectively) were negatively related to
axis 1. MRPP showed that community structure varied among
stands in different stages of development (p = 0.057). Pair-wise
comparisons showed that pole stands differed from mature stands
(p = 0.039) while mature and pole, and mature and old-growth
stands did not differ (p > 0.10). In contrast, soil texture did not
appear to be related to community structure (MRPP, p = 0.102).
4.6. Relationships among community attributes, understory species
and stand origin
The second ordination of understory species resulted in a threedimensional NMS solution that captured 74.4% of the total
variation (40.0% of the variation on axis 1, 18.9% on axis 2;
Fig. 3b), had a final stress of 8.60 and demonstrated greater
structure than expected by chance (Monte Carlo, a = 0.05). Primary
and second-growth stands exhibited strong differences in understory plant community composition and structure (MRPP;
p = 0.019). While differences between stands in different developmental stages were not substantial (MRPP; p = 0.150), stands
that varied in soil texture (coarse loamy vs. loamy and fine to very
fine) exhibited significant differences in understory plant communities (MRPP; p = 0.030). Because soil texture classes are
comparably distributed among primary and second-growth
stands, we do not expect these differences to impact comparison
of these stand types.
Primary stands were contrasted with second-growth stands
primarily along axis 1 (Fig. 3b) and positively associated with
higher densities of P. glauca saplings and greater percent cover of
Lycopodium annotinum (r = 0.72 and 0.55, respectively; Table 5).
Viola pubescens (r = 0.84), Claytonia caroliniana (r = 0.83),
Mertensia paniculata (r = 0.68), Trillium spp. (r = 0.67), Uvularia
grandiflora (r = 0.63), Lonicera canadensis (r = 0.63), Streptopus
roseus (r = 0.61), Anenome quinquefolia (r = 0.61), Dicentra spp.
(r = 0.59), Asarum canadensis (r = 0.58), Athyrium felix-femina
(r = 0.56), Ribes spp. (r = 0.52) and Sanguinaria canadensis
(r = 0.51) were negatively associated with axis 1 and the
locations of primary stands (Table 5). Characteristics indicating
an importance of yellow birch and conifer trees (%BA, BA and TPH)
were positively related to axis 1 and the locations of primary
stands (r = 0.72, 0.70 and 0.67, respectively for yellow birch; and
r = 0.63, 0.72 and 0.54, respectively for conifers). Average Ohorizon depth (r = 0.69), O-horizon weight (r = 0.57), %BA of other
hardwoods (r = 0.55) and CWD in decay class two (DC2) (r = 0.53)
were also positively related to axis 1.
Percent cover of yellow birch (r = 0.60), and first-year birch
(yellow birch or white birch) seedlings (r = 0.60), density of Corylus
cornuta (r = 0.60), cover of A. rubrum (r = 0.56) and Carex arctata
(r = 0.55) were positively related to axis 2, while percent cover of
Arisaema triphyllum (r = 0.58), Dicentra spp. (r = 0.53), A.
Table 5
Understory plant species correlated (r 0.50) with ordination axes by guild.
Primary
Second-growth
Axis 1 Axis 2
Fern allies (%cover)
Lycopodium annotinum
2.53 (1.26)
0.97 (0.54)
0.55
0.43
Ferns (%cover)
Athyrium felix-femina
3.21 (0.88)
6.19 (1.76)
0.56
0.33
Spring ephemerals (%cover)
Claytonia caroliniana
0.14 (0.08)
Dicentra spp.
0.00 (0.00)
2.55 (0.60)
0.88 (0.73)
0.83
0.59
0.44
0.53
Early-summer forbs (%cover)
Anenome quinquefolia
0.03
Asarum canadensis
0.00
Mertensia paniculata
0.00
Sanguinaria canadensis
0.00
Streptopus roseus
1.58
Trillium spp.
0.07
Uvularia grandiflora
0.00
Viola pubescens
0.06
0.71
0.04
0.04
0.06
3.02
0.27
0.77
0.80
(0.25)
(0.04)
(0.03)
(0.05)
(0.33)
(0.08)
(0.57)
(0.29)
0.61
0.58
0.68
0.51
0.61
0.67
0.63
0.84
0.03
0.51
0.48
0.21
0.49
0.04
0.51
0.38
Late-summer forbs (%cover)
Carex arctata
0.03 (0.03)
0.27 (0.10)
0.18
0.55
Shrubs 1 m tall (%cover)
Lonicera canadensis
Ribes spp.
0.19 (0.09)
0.06 (0.04)
0.63
0.52
0.23
0.46
Shrubs >1 m (stems ha1)
Corylus cornuta
899.22 (570.80) 2343.5 (1059.10) <0.01
0.60
Trees seedlings (%cover)
Betula alleghaniensis
0.24 (0.08)
0.14 (0.05)
0.49
0.60
Other hardwoods
Acer rubrum
Betula spp.
0.01 (0.01)
0.02 (0.02)
0.14 (0.09)
0.01 (0.01)
0.14
0.16
0.56
0.60
39.79 (15.24)
7.96 (5.21)
0.55
0.11
Conifers
Picea glauca
(0.03)
(0.00)
(0.00)
(0.00)
(0.36)
(0.04)
(0.00)
(0.05)
0.00 (0.00)
0.00 (0.00)
Cover or density estimates are given by type (mean and standard error), as well as
Pearson correlations with plot axis scores. Taxonomic authority is Flora of North
America, 1993+.
canadensis (r = 0.51), U. grandiflora (r = 0.51) and F. nigra
seedlings (r = 0.51) were negatively related to axis 2. Shrub
density (r = 0.72), CWD in DC5 (r = 0.57), elevation (r = 0.56), and
mineral soil (r = 0.52) were positively related to axis 2, and spring
ephemerals were negatively related to axis 2 (r = 0.58). Percent
diffuse light transmittance (%light) at 2 m was positively
associated with axis 2 (r = 0.76, p = 0.027), but only after the
removal of an outlying second-growth stand (BH).
4.7. Indicator species analysis
Analysis of herbaceous (non-woody) indicator species identified four species closely associated with second-growth stands
including one spring ephemeral (C. caroliniana; p = 0.025), and
three early-summer forbs (A. quinquefolia, S. roseus and V.
pubescens; p = 0.034, 0.026, and 0.060, respectively). Only one
species, an evergreen fern ally, was marginally associated with
primary stands (L. annotinum) (p = 0.092). The importance value of
the indicator species was at least 40 points higher in the group that
they indicate with the exception of S. roseus, which was 32 points
higher in second-growth stands than primary stands.
5. Discussion
5.1. Overstory composition and structure
Although few structural attributes varied between primary and
second-growth stands when values were aggregated across
species, both yellow birch and conifer species were substantially
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
more abundant within primary stands. Furthermore, at the
multivariate level, primary stands were separated from secondgrowth stands principally by a gradient in the abundance of yellow
birch and conifers such that excluding these variables (yellow
birch and conifer BA, %BA and TPH) from the ordination weakened
the differences between types (MRPP, p = 0.111). The lack of yellow
birch and conifers in second-growth stands may be a result of highgrade logging occurring subsequent to the cutover (Stott, 1943;
Nyland, 1992) and the complex life histories of these species
(Burns and Honkala, 1990). While yellow birch and conifers were
selectively high-graded from second-growth stands, the regeneration strategies for yellow birch and conifer species are also
complex. The absence of microsites suitable for the establishment
of light-seeded species (e.g., exposed mineral soil, tip-up mounds)
and a lack of site preparation prior to logging could have led to low
levels of regeneration following the cutover (Carlton and Bazzaz,
1998; Lorenzetti et al., 2008). However, these conditions are often
created during harvesting activities, particularly those that
occurred during the cutover. Therefore, low levels of regeneration
following the cutover may be more strongly related to dispersal
limitation following the removal of reproductively mature seed
trees. Our results conflict with previous studies that identify only
structural and few compositional differences between old-growth
and second-growth stands (Hale et al., 1999; McGee et al., 1999);
however, our work is consistent with results from northern
Wisconsin and upper Michigan (Goodburn and Lorimer, 1999).
5.2. Coarse woody debris and snags
The abundance and distribution of CWD and snags may vary
both among developmental stages and as a result of the removal of
tree boles during harvesting (Tyrrell and Crow, 1994). Consistent
with previous studies, we observed differences in the volume and
distribution of CWD among size and decay classes between stand
types. However, while we observed substantially greater variability in volume in DC5 among primary stands than secondgrowth stands, primary stands also had greater volumes on
average and higher levels of within-stand spatial variability for
intermediate decay and size classes. The ordination of structural
characteristics showed that CWD in DC3 was related to %large and
Modal D, which indicate later stages of development. In contrast,
previous studies comparing old-growth forests to younger
second-growth forests reported pronounced differences in large
size classes and substantially lower total CWD volumes for evenaged second-growth stands (Goodburn and Lorimer, 1998; McGee
et al., 1999). Hale et al. (1999) also observed differences between
stand types in mid-size classes and suggested the relatively lower
rates of decomposition of decay-resistant coniferous trees, and
larger maximum tree sizes observed in the other comparative
studies led to the greater volumes of wood in larger size classes
and later stages of decay in old-growth hemlock-hardwood
forests relative to stands lacking hemlock (e.g., Harmon and Hua,
1991).
The density of snags detected in our study – similar between
primary and secondary stands – was higher than densities
reported for other old-growth stands in Minnesota (Hale et al.,
1999) but similar to values reported for old-growth forests
elsewhere (McGee et al., 1999). High densities of snags observed
at our sites relative to other study areas may also reflect a more
severe of wind-disturbance in northeastern Minnesota (D’Amato
et al., 2008); however, the discrepancy might also be related to site
quality as it is influenced by soil texture. Less fertile, northern sites
characterized by coarser-textured soils may experience greater
snag densities because these sites may have a higher incidence of
trunk-rotting disease (Ward et al., 1966), leading to stem breakage,
as well as a lower incidence of tree tipping (Kabrick et al., 1997).
2565
5.3. Understory vegetation
The abundance of tree seedlings and saplings did not vary for
sugar maple, yellow birch, conifers, other hardwoods or shrubs
between primary and second-growth stands; however, tree
seedlings and saplings were associated with the composition
and the structure of the overstory (Modal D and %large) at the
multivariate level. For the first ordination of community attributes,
conifer and yellow birch saplings, shrub cover and shrub density
were associated with earlier stages of development along axis 1. In
contrast, sugar maple seedlings and saplings were positively
associated with Modal D, %large and stands in later developmental
stages. While the relationship between conifer and yellow birch
saplings, and stand structure observed in the first ordination was
not related to light transmittance, it is feasible that the canopy may
have closed since the conifer and yellow birch saplings established.
In contrast, yellow birch seedlings were related to axis 2, and the
locations of primary stands and the abundance of yellow birch in
the overstory. Shrub density, CWD in DC5, A. rubrum seedlings,
exposed mineral soil and %light was correlated with axis 2, while P.
glauca was associated with axis 1, and the abundance of conifer
trees in the second ordination (of understory species). Thus,
disturbances that increase the availability of resources, such as
light, temporarily may be necessary to maintain populations of
shade-intolerant tree species (e.g., Connell, 1979). However, the
relationship between yellow birch seedlings and %light appears to
be contingent not only on the presence of microsites (e.g., exposed
mineral soil or CWD in advanced stages of decay) but also upon the
presence of yellow birch seed trees in the overstory. Similarly, the
observed association among P. glauca saplings, conifer BA and
primary stands may be related to increased seed availability in
these stands.
Graminoid species were more abundant in second-growth
stands, and the distribution of graminoid cover was more
heterogeneous both within and among second-growth stands.
Both white-tailed deer (Odocoileus virginianus) herbivory and
exotic earthworm invasions have been associated with an
increased importance of sedge species such as Carex pensylvanica
in northern hardwood forests (Hale et al., 2006; Wiegmann and
Waller, 2006; Holdsworth et al., 2007a). Deer herbivory and
earthworm invasion severity are both enhanced by landscape
fragmentation (Augustine and Frelich, 1998; Holdsworth et al.,
2007b). Because second-growth stands are closer to roads, it is
possible that the increase in graminoid cover, and the variability of
graminoid cover within stands, is an indirect effect of road density
and due to the effects of earthworms and deer herbivory rather
than a direct legacy of historical logging. However, increased
variability of graminoid cover among second-growth stands
corresponds to the greater range of developmental stages among
second-growth stands as well as light transmittance. Furthermore,
in the ordination of understory species, C. arctata cover and %light
were positively associated with axis 2, which was also modestly
negatively related to Modal D and positively related to C.
pensylvanica cover. Thus, graminoid cover also appears to be
higher in stands in earlier developmental stages with higher levels
of light transmittance resulting in greater levels of landscape-scale
variability for second-growth stands.
The close associations among understory species, community
attributes and guilds suggest that understory species are
partitioning resource gradients that are driven by the composition
of the overstory and CWD volume (Fig. 3). Evergreen conifer
species in the primary stands (P. glauca, T. occidentalis and A.
balsamea) may function to lower light levels and temperatures
early in the spring, reducing the abundance of spring ephemerals
and early-summer species locally. Furthermore, the high-lignin
and low-nitrogen concentration of conifer foliage may function to
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J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
slow rates of decomposition resulting in deeper O-horizons
(Melillo et al., 1982), while greater nitrogen and calcium
concentrations of sugar maple leaf litter functions to increase
rates of decomposition and nutrient cycling (Reich et al., 2005).
Such relationships among overstory composition, resource availability and understory community composition have been
observed repeatedly in hemlock-hardwood forests (Mladenoff,
1987; Canham et al., 1994; Beatty, 1984; Boettcher and Kalisz,
1990; Ferrari, 1999). Moreover, greater volumes of CWD may
contribute to slowing rates of decomposition and nitrogen cycling
in primary stands (Campbell and Gower, 2000). In the absence of
resource regulation by conifer species and CWD, L. annotinum may
otherwise be out-competed by spring ephemeral and earlysummer species. Alternatively, it is possible that logging directly
reduced populations of L. annotinum in second-growth forests by
disturbing the O-horizon and surface soils, and that the association
between ground flora and tree species composition is merely
coincidental (Zenner and Berger, 2008).
5.4. Diversity and cover
Second-growth stands contained 162% of the quadrat richness
of forest herbs of primary stands, 197% of the cover of primary
stands. These results contrast nearly oppositely with those of Duffy
and Meier (1992), who observed 165% of quadrat richness and
252% of the cover of second-growth stands in primary stands in the
southern Appalachians, as well as studies comparing postagricultural understory communities to mature second-growth
stands that were never cleared for agriculture (e.g., Vellend et al.,
2007). However our results are consistent with other reports from
the Lake States (Metzger and Schultz, 1981, 1984; Scheller and
Mladenoff, 2002), and the central Appalachians (Gilliam et al.,
1995) that show increased herb diversity and cover in younger
stands. Greater levels of herbaceous beta diversity and a lower rate
of species accumulation over area in primary stands (Fig. 2) suggest
that while logging has not decreased plant diversity in secondgrowth stands overall, there are differences in the processes
structuring diversity between primary and second-growth stands.
Because the majority of second-growth stands are in earlier stages
of development than primary stands, these patterns and those
observed for tree seedlings may be partially explained by the
intermediate disturbance hypothesis (Connell, 1979). However,
resource regulation by conifers and CWD, as well as heterogeneity
of key attributes, and dispersal limitation may also contribute to
the differences in species accumulation rates that we observed
between stand types.
5.5. Summary and management implications
The focus of natural disturbance-based forest management in
northern hardwood forests has been to restore the structures and
processes characteristic of old-growth forests to younger secondgrowth stands. The majority of the primary stands were in the oldgrowth stage of development while second-growth stands
spanned the pole, mature and old-growth developmental classes,
indicating that although second-growth stands can develop oldgrowth characteristics over time they remain in various stages of
recovery that likely vary with the time since they were last highgraded. In addition to the differences in the distribution of growth
stages between primary and second-growth stands on the
landscape, important differences in species composition and key
community attributes were observed. Specifically, second-growth
stands had lower abundances of yellow birch and conifer species
and reduced structural and environmental heterogeneity within
stands; furthermore, these variables were associated with changes
in the composition and structure of the understory plant
communities. This simplification of community structure in
second-growth stands may be reinforced by typical patterns of
disturbance and succession, leading to stands that are less resilient
to a changing climate, future harvesting, and other stressors. The
onset of this disparity may be associated not as much with the
original cutover as with the subsequent high-grade logging for
yellow birch and conifers. However, because of our low sample size
and lack of time series data we do not have enough information to
correctly identify the type of model (i.e., linear, non-linear,
hysteresis), or locations of critical thresholds.
Efforts to restore the composition, structure and processes of
reference primary stands to second-growth northern hardwood
forests should therefore focus not only on restoring a stage of
structural development (i.e., old growth) or level of diversity, but
prioritize the establishment of a patchy distribution of yellow birch
and conifer species and overstory–understory feedbacks within
second-growth stands. This may require introducing a moderateseverity disturbance, and temporary successional retrogression
(Woods, 2004; Hanson and Lorimer, 2007), to second-growth
stand in later stages of structural development coupled with
planting or direct seeding and low-intensity site preparation
(Lorenzetti et al., 2008). If the system is characterized by
hysteresis, the potential for multiple states over a range of driving
conditions, then adequate restoration of second-growth stands
may require restoring yellow birch and conifer abundances and
heterogeneity beyond those extant in current primary stands.
Intermediate treatments, such as thinning, crop-tree management
(Perkey et al., 1994) and crown release (Singer and Lorimer, 1997)
could be used to favor these species over time, as well as to
accelerate the development of old-growth stand structure after
establishment.
Acknowledgements
Funding for the project was provided by the National Oceanic
and Atmospheric Administration and Minnesota’s Lake Superior
Coastal Program. We are grateful to Lake County Forestry and The
Nature Conservancy of Minnesota, and the Manitou Collaborative
for making this research possible. For their contributions to the
project we would like to thank C. Dunham, D. Spina, J.E. Peck, B.
Boyce, C. Ferguson, N. Bygd and L. Desotelle. We also thank two
anonymous reviewers for helpful comments on a previous version.
References
Arrhenius, O., 1921. Species and area. Journal of Ecology 9, 95–99.
Attiwill, P.M., 1994. The disturbance of forest ecosystems – the ecological basis for
conservative management. Forest Ecology and Management 63, 247–300.
Augustine, D.J., Frelich, L.E., 1998. Effects of white-tailed deer on populations of an
understory forb in fragmented deciduous forests. Conservation Biology 12,
995–1004.
Barbier, S., Gosselin, F., Balandier, P., 2008. Influence of tree species on understory
vegetation diversity and mechanisms involved – a critical review for temperate
and boreal forests. Forest Ecology and Management 254, 1–15.
Beatty, S.W., 1984. Influence of microtopography and canopy species on spatial
patterns of forest understory plants. Ecology 65, 1406–1419.
Boettcher, S.E., Kalisz, P.J., 1990. Single-tree influence on soil properties in the
mountains of eastern Kentucky. Ecology 71, 1365–1372.
Burns, R.M., Honkala, B.H. (Eds.), 1990. Silvics of North America.. U.S. Department
of Agriculture, Forest Service, Washington, DC.
Campbell, J.L., Gower, S.T., 2000. Detritus production and soil N transformations in
old-growth eastern hemlock and sugar maple stands. Ecosystems 3, 185–192.
Canham, C.D., Finzi, A.C., Pacala, S.W., Burbank, D.H., 1994. Causes and consequences of resource heterogeneity in forests – interspecific variation in light
transmission by canopy trees. Canadian Journal of Forest Research 24, 337–349.
Carlton, G.C., Bazzaz, F.A., 1998. Regeneration of three sympatric birch species on
experimental hurricane blowdown microsites. Ecological Monographs 68,
99–120.
Connell, J.H., 1979. Intermediate-disturbance hypothesis. Science 204, 1345.
Cornett, M.W., Reich, P.B., Puettmann, K.J., 1997. Canopy feedbacks and microtopography regulate conifer seedling distribution in two Minnesota conifer-deciduous forests. Ecoscience 4, 353–364.
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
Crow, T.R., Buckley, D.S., Nauertz, E.A., Zasada, J.C., 2002. Effects of management on
the composition and structure of northern hardwood forests in Upper Michigan.
Forest Science 48, 129–145.
Cummings, J.F., Grigal, D.F., 1981. Legend to map: soils and land surfaces of
Minnesota. University of Minnesota Agricultural Experiment Station Soil Series
No. 110, Misc. Puplication 11.
D’Amato, A.W., Orwig, D.A., Foster, D.R., 2008. The influence of successional processes and disturbance on the structure of Tsuga canadensis forests. Ecological
Applications 18, 1182–1199.
Dahir, S.E., Lorimer, C.G., 1996. Variation in canopy gap formation among developmental stages of northern hardwood stands. Canadian Journal of Forest
Research 26, 1875–1892.
Drever, C.R., Peterson, G., Messier, C., Bergeron, Y., Flannigan, M., 2006. Can forest
management based on natural disturbances maintain ecological resilience?
Canadian Journal of Forest Research 6, 2285–2299.
Duffy, D.C., Meier, A.J., 1992. Do Appalachian herbaceous understories ever recover
from clearcutting? Conservation Biology 6, 196–201.
Dufrêne, M., Legendre, P., 1997. Species assemblages and indicator species: the
need for a flexible asymmetrical approach. Ecological Monographs 61,
345–366.
Eyre, F.H., 1939. Silvicultural management of northern hardwoods. Journal of
Forestry 37, 719–721.
Ferrari, J.B., 1999. Fine-scale patterns of leaf litterfall and nitrogen cycling in an oldgrowth forest. Canadian Journal of Forest Research 29, 291–302.
Flora of North America Editorial Committee (Eds.), 1993+. Flora of North America
North of Mexico. 12+ vols. New York and Oxford.
Franklin, J.F., Spies, T.A., Van Pelt, R., Carey, A.B., Thornburgh, D.A., Berg, D.R.,
Lindenmayer, D.B., Harmon, M.E., Keeton, W.S., Shaw, D.C., Bible, K., Chen,
J.Q., 2002. Disturbances and structural development of natural forest ecosystems with silvicultural implications, using Douglas-fir forests as an example.
Forest Ecology and Management 155, 399–423.
Fraterrigo, J.M., Rusak, J.A., 2008. Disturbance-driven changes in the variability of
ecological patterns and processes. Ecology Letters 11, 756–770.
Frelich, L.E., 1995. Old forest in the Lake States today and before European settlement. Natural Areas Journal 15, 157–167.
Frelich, L.E., Cornett, M.W., White, M.A., 2005. Controls and reference conditions in
forestry: the role of old-growth and retrospective studies. Journal of Forestry
103, 339–344.
Frelich, L.E., Lorimer, C.G., 1991. Natural disturbance regimes in hemlock hardwood
forests of the upper Great-Lakes region. Ecological Monographs 61, 145–164.
Frelich, L.E., Reich, P.B., 2003. Perspectives on development of definitions and values
related to old-growth forests. Environmental Reviews 11, 9–22.
George, L.O., Bazzaz, F.A., 1999. The fern understory as an ecological filter: growth
and survival of canopy-tree seedlings. Ecology 80, 846–856.
Gilliam, F.S., Turrell, N.L., Adams, M.B., 1995. Herbaceous-layer and overstory
species in clear-cut and mature central Appalachian hardwood forests. Ecological Applications 5, 947–955.
Givnish, T.J., 1987. Comparative studies of leaf form – assessing the relative roles of
selective pressures and phylogenetic constraints. New Phytologist 106,
131–160.
Goodburn, J.M., Lorimer, C.G., 1998. Cavity trees and coarse woody debris in oldgrowth and managed northern hardwood forests in Wisconsin and Michigan.
Canadian Journal of Forest Research 28, 427–438.
Goodburn, J.M., Lorimer, C.G., 1999. Population structure in old-growth and managed northern hardwoods: an examination of the balanced diameter distribution concept. Forest Ecology and Management 118, 11–29.
Hale, C.M., Frelich, L.E., Reich, P.B., 2006. Changes in hardwood forest understory
plant communities in response to European earthworm invasions. Ecology 87,
1637–1649.
Hale, C.M., Pastor, J., Rusterholz, K.A., 1999. Comparison of structural and compositional characteristics in old-growth and mature, managed hardwood forests of
Minnesota, USA. Canadian Journal of Forest Research 29, 1479–1489.
Hanson, J.J., Lorimer, C.G., 2007. Forest structure and light regimes following
moderate wind storms: implications for multi-cohort management. Ecological
Applications 17, 1325–1340.
Harmon, M.E., Hua, C., 1991. Coarse woody debris dynamics in two old-growth
ecosystems – comparing a deciduous forest in China and a conifer forest in
Oregon. Bioscience 41, 604–610.
Harmon, M.E., Sexton, J., 1996. Guidelines for measurements of woody detritus in
forest ecosystems. U.S. LTER Network Office, University of Washington, Seattle,
WA, USA Publication No. 20, p. 73.
Helms, J.A., 1998. The Dictionary of Forestry. The Society of American Foresters,
Bethesda, MD, USA.
Holdsworth, A.R., Frelich, L.E., Reich, P.B., 2007a. Effects of earthworm invasion on
plant species richness in northern hardwood forests. Conservation Biology 21,
997–1008.
Holdsworth, A.R., Frelich, L.E., Reich, P.B., 2007b. Regional extent of an ecosystem
engineer: earthworm invasion in northern hardwood forests. Ecological Applications 17, 1666–1677.
Holling, C.S., 1973. Resilience and stability of ecological systems. Annual Review of
Ecology and Systematics 4, 1–23.
Hurlbert, S.H., 1984. Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54, 187–211.
Kabrick, J.M., Clayton, M.K., Mcsweeney, K., 1997. Spatial patterns of carbon and
texture on drumlins in northeastern Wisconsin. Soil Science Society of America
Journal 61, 541–548.
2567
Keeton, W.S., 2006. Managing for late-successional/old-growth characteristics in
northern hardwood-conifer forests. Forest Ecology and Management 235,
129–142.
Kruskal, J.B., 1964. Nonmetric multidimensional scaling: a numerical method.
Psychometrika 29, 115–129.
Levene, H., 1960. Robust tests for equality of variance. In: Olkin, I. (Ed.), Contributions to Probability and Statistics. Stanford University Press, Palo Alto, CA,
USA, pp. 278–292.
Lorenzetti, F., Delagrange, S., Bouffard, D., Nolet, P., 2008. Establishment, survivorship, and growth of yellow birch seedlings after site preparation treatments in
large gaps. Forest Ecology and Management 254, 350–361.
Lorimer, C.G., Frelich, L.E., 1994. Natural disturbance regimes in old-growth northern hardwoods – implications for restoration efforts. Journal of Forestry 92,
33–38.
Lorimer, C.G., Frelich, L.E., 1998. A structural alternative to chronosequence analysis
for uneven-aged northern hardwood forests. Journal of Sustainable Forestry 6,
347–366.
Mather, P.M., 1976. Computational Methods of Multivariate Analysis in Physical
Geography. John Wiley and Sons, London.
McCune, B., Grace, J.B., 2002. Analysis of Ecological Communities. MjM Software
Design, Gleneden Beach, OR.
McCune, B., Mefford, M.J., 1999. PC-ORD. Multivariate analysis of ecological data.
Version 4.0. MjM Software, Gleneden Beach, Oregon, USA.
McGee, G.G., Leopold, D.J., Nyland, R.D., 1999. Structural characteristics of oldgrowth, maturing, and partially cut northern hardwood forests. Ecological
Applications 9, 1316–1329.
Melillo, J.M., Aber, J.D., Muratore, J.F., 1982. Nitrogen and lignin control of hardwood
leaf litter decomposition dynamics. Ecology 63, 621–626.
Metzger, F., Schultz, J., 1981. Spring ground layer vegetation 50 years after harvesting in northern hardwood forests. American Midland Naturalist 105, 44–50.
Metzger, F., Schultz, J., 1984. Understory response to 50 years of management of a
northern hardwood forest in upper Michigan. American Midland Naturalist
112, 209–223.
Minchin, P.R., 1987. An evaluation of the relative robustness of techniques for
ecological ordination. Vegetatio 69, 89–107.
Mladenoff, D.J., 1987. Dynamics of nitrogen mineralization and nitrification in
hemlock and hardwood treefall gaps. Ecology 68, 1171–1180.
Moore, M.R., Vankat, J.L., 1986. Response of the herb layer to the gap dynamics of a
mature beech-maple forest. American Midland Naturalist 115, 336–347.
Neyman, J., Pearson, E.S., 1933. On the problem of the most efficient tests of
statistical hypotheses. Philosophical Transactions of the Royal Society of London 231, 289–337.
Nyland, R.D., 1992. Exploitation and greed in eastern hardwood forests: will
foresters get another chance? Journal of Forestry 90, 33–37.
Perkey, A.W., Wilkins, B.L., Smith, H.C., 1994. Crop tree management in eastern
hardwoods. In: USDA Forest Service, Northeastern Area State & Private Forestry,
Forest Resources Management NA-TP-19-93, Morgantown, WV.
Reich, P.B., Oleksyn, J., Modrzynski, J., Mrozinski, P., Hobbie, S.E., Eissenstat, D.M.,
Chorover, J., Chadwick, O.A., Hale, C.M., Tjoelker, M.G., 2005. Linking litter
calcium, earthworms and soil properties: a common garden test with 14 tree
species. Ecology Letters 8, 811–818.
Roberts, M.R., Gilliam, F.S., 1995. Patterns and mechanisms of plant diversity in
forested ecosystems – implications for forest management. Ecological Applications 5, 969–977.
Rusterholz, K.A., 1996. Identification and protection of old growth on state-owned
land in Minnesota. In: Davis, M.B. (Ed.), Eastern Old Growth Forests: Prospects
for Rediscovery and Recovery. Island Press, Washington, DC, USA, pp. 291–304.
Scheller, R.M., Mladenoff, D.J., 2002. Understory species patterns and diversity in
old-growth and managed northern hardwood forests. Ecological Applications
12, 1329–1343.
Schultz, B.B., 1985. Levene test for relative variation. Systematic Zoology 34,
449–456.
Seymour, R.S., White, A.S., deMaynadier, P.G., 2002. Natural disturbance regimes in
northeastern North America – evaluating silvicultural systems using natural
scales and frequencies. Forest Ecology and Management 155, 357–367.
Singer, M.T., Lorimer, C.G., 1997. Crown release as a potential old-growth restoration approach in northern hardwoods. Canadian Journal of Forest Research 27,
1222–1232.
Spies, T.A., Franklin, J.F., 1988. Old growth and forest dynamics in the Douglas-fir
region of western Oregon and Washington. Natural Areas Journal 8, 190–
201.
Stearns, F.W., 1997. History of the Lake States Forests: Natural and human impacts.
In: Vassiech J. Michael, Webster, Henry H. (Eds.), Lake States Regional Forest
Resources Assessment: Technical Papers. Gen. Tech Rep. NC-189. St. Paul, MN:
U.S.D.A. Forest Service, North Central Forest Experiment Station, pp. 8–29.
Stott, C.B., 1943. Increasing production of critical lumber grades by selective cutting.
Journal of Forestry 41, 734–739.
Tikkanen, B., Duhant, M., From, S., 1995. How we Remember: Stories and Recollections of Finland, Minnesota’s first century 1895–1995. Arrowhead Printing, Inc.,
Superior, WI.
Tyrrell, L.E., Crow, T.R., 1994. Structural characteristics of old-growth hemlockhardwood forests in relation to age. Ecology 75, 370–386.
Ward, W.W., Berglund, J.V., Borden, F.Y., 1966. Soil-site characteristics and occurrence of sugar maple canker in Pennsylvania. Ecology 47, 541–548.
Welles, J.M., Norman, J.M., 1991. Instrument for indirect measurement of canopy
architecture. Agronomy Journal 83, 818–825.
2568
J.I. Burton et al. / Forest Ecology and Management 258 (2009) 2556–2568
Wiegmann, S.M., Waller, D.M., 2006. Fifty years of change in northern upland forest
understories: identity and traits of ‘‘winner’’ and ‘‘loser’’ plant species. Biological Conservation 129, 109–123.
Woods, K.D., 2004. Intermediate disturbance in a late-successional hemlock-northern hardwood forest. Journal of Ecology 92, 464–476.
Vellend, M., Verheyen, K., Flinn, K.M., Jacquemyn, H., Kolb, A., Van Calster, H.,
Peterken, G., Graae, B.J., Bellemare, J., Honnay, O., Brunet, J., Wulf, M., Gerhardt,
F., Hermy, M., 2007. Homogenization of forest plant communities and weakening of species–environment relationships via agricultural land use. Journal of
Ecology 95, 565–573.
Zar, J.H., 1974. Biostatistical Analysis. Prentice Hall, Englewood Cliffs, NJ, USA, p. 620.
Zenner, E.K., 2004. Does old-growth condition imply high live-tree structural
complexity? Forest Ecology and Management 195, 243–258.
Zenner, E.K., Berger, A.L., 2008. Influence of skidder traffic and canopy removal
intensities on the ground flora in a clearcut-with-reserves northern hardwood
stand in Minnesota, USA. Forest Ecology and Management 256, 1785–1794.
Zimmerman, G.M.H., Goetz, H., Mielke, P.W.J., 1985. Use of an improved statistical
method for group study effects of prairie fire. Ecology 66, 606–611.
Zon, R., 1925. Forestry and land development in the Lake States. The Journal of Land
and Public Utility Economics 1, 36–43.