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2011 SOUTHEASTERN NATURALIST 10(1):25–38
Effects of Power-line Maintenance on Forest Structure in a
Fragmented Urban Forest, Raleigh, NC
Amanda S. Powell1 and Erin S. Lindquist2, *
Abstract - With the increase in urban development, forest fragments are becoming more
prevalent. In urban areas, there is a tendency to hide power-lines within or on the edges
of these fragmented forests; however, it is unknown how the maintenance of vegetation
under and along power-lines impacts the forest composition and structure of an adjacent
fragmented, urban forest. An urban, fragmented maple-oak-hickory forest is located on
the Meredith College campus, Raleigh, NC. A 1-ha plot with a hundred 10- x 10-m subplots
was established in 2007 to initiate a long-term project supporting undergraduate
research. An adjacent meadow is cut and maintained regularly up to the forest and plot
edge for power-line clearance and access. We identified, tagged, and measured all of the
trees with a diameter at breast height (DBH) ≥ 5 cm in this permanent plot, and compared
the tree species richness (S), Shannon-Weiner diversity index (H), Sorenson’s similarity
index (Ss), DBH, stem density, and basal area along the 100-m gradient from the forest
edge. We also used a non-metric multidimensional scaling (NMS) analysis to describe
how species composition changed along the gradient. Our findings showed that S, H, and
Ss did not change along the 100-m gradient. The NMS confirmed that species composition
was not different in the edge subplots (0–10 m from edge) compared to all other subplots
and therefore was not impacted by continual, local disturbance along forest edges.
However, we found that forest structure changed along the gradient with the exception of
mean DBH; stem density and total basal area varied along the 100-m gradient. There was
greater stem density along the edge of the forest (0–5 m and 10–20 m from edge) compared
to the other interior subplots. Some of the interior subplots (10–20 m and 60–70 m
from the edge) had a higher total basal area than the remaining plots. As expected, we also
found that there was a negative linear relationship between DBH and stem density for all
subplots. Our results confirm trends found in previous studies that community structure
parameters (stand density and basal area) differ between forest edges and their respective
forest interiors, but did not agree with previous research, which found species composition
to be affected by edges. We believe the regular pruning of the forest edge adjacent
to the power-lines explains our observed differences in forest structure, but tree species
richness, diversity, similarity, and composition may be determined by the disturbance of
larger-scale ecological processes. Our results show how power-line placement within a
fragmented urban forest can affect the structure of the adjacent forest, and we recommend
that the ecological effects of power-line corridors should be further investigated and incorporated
into the larger body of literature on forest fragmentation.
Fragmented edges are becoming more widespread in urban areas. In the
United States, about 44% of trees in forests are located 90 m from the edge of
the forest (McDonald and Urban 2004, Riitters et al. 2002). As forests become
1Department of Zoology, University of Wisconsin - Madison, Madison, WI 53706.2Department
of Biological Sciences, Meredith College, 3800 Hillsborough Street, Raleigh,
NC 27607-5298. *Corresponding author - firstname.lastname@example.org.
26 Southeastern Naturalist Vol. 10, No. 1
more fragmented and irregular in shape, edge habitat continues to increase and
forest structure and composition are affected (Ries et al. 2004, Williams-Linera
1990). Forests become fragmented as power-line corridors, roads, gas lines, and
other infrastructure are established (Benítez-López et al. 2010, Laurance et al.
2009, Luken et al.1991a). Although a significant number of studies have investigated
how the creation of forest edges impact ecosystem function (Harper et
al. 2005) and biodiversity (Fahrig 2003), there is a need for additional studies to
elucidate how local factors such as climate, edge type, and forest type affect the
changes in forest composition and structure (Harper et al. 2005). For example,
Luken et al. (1991a) found that mature tree stem densities were higher along
forest edges adjacent to pastures and clear-cuts compared to power-line corridors,
but edges adjacent to power-line corridors had a higher density and basal
area for saplings and seedlings.
Forest habitat that is cleared for roads and electric or communication lines
can significantly increase the exposure to wind and/or other abiotic factors along
forest fragment edges (Pohlman et al. 2009). For aesthetic purposes, there may
be an attempt to hide the power-lines in urban forests and this may contribute
to forest fragmentation and the development of the edge (Luken et al.1991a).
Along forest edges where power-lines are located, the vegetation is maintained
to keep the area under the lines clear for maintenance purposes and keep the
vegetation out of the lines (Johnstone 1990, Luken et al. 1991a). Tree stems and
branches along the forest edge are regularly pruned or removed and the adjacent
herbaceous vegetation is mowed or removed by herbicidal treatments. Where
the vegetation is mowed along forest edges, the root system of trees is often not
killed (Johnstone 1990). Thus, mowing allows for multiple shoots to grow from
the base (Johnstone 1990), and may lead to higher stem densities along the edge
compared to the interior areas ( ≥10 m) of the forest (Luken et al. 1991b).
Previous research indicates that forest edges located along power-line corridors
have a higher stem density up to 10–15 m into the forests (Luken et al.
1991a). However, Luken et al. (1991a, 1991b, 1992) only investigated forest
structure and composition 25 m into the forest from the power-line corridor, and
therefore it is not known if edge effects are found further into the forest. In addition,
research conducted by Luken et al. (1991a, 1991b, 1992) was done in a rural
landscape with forest remnants. It is unknown how fragmented urban forests
respond to power-line corridors.
Our research was conducted in a southeastern deciduous forest to investigate
how the composition and structure of a fragmented urban forest is affected by
regular maintenance of a forest edge for power-lines. According to one study conducted
in the Piedmont of North Carolina (McDonald and Urban 2006), which is
in close proximity to our study site but not as urban as our study area, edge effects
were found to affect the tree species composition up to 5 m from the forest edge.
McDonald and Urban (2006) did not clarify how their study’s forest edges were
created, but we assume that the majority were not along power-line corridors. At
our study site, we predicted that tree species richness would be greater along the
edge and that the composition of edge plots would be dissimilar when compared
2011 A.S. Powell and E.S. Lindquist 27
to the interior subplots. Furthermore, we expected to find lower diameter-atbreast
height (DBH), higher stem density, and lower basal area along the edge
when compared to the interior.
We conducted this study in a fragmented urban forest on the Meredith College
campus, Raleigh, in the piedmont of North Carolina (35°48'22.05"N,
78°41'31.39"W) (Fig. 1). Meredith College purchased the study area, which is
approximately 22.26 ha in size, in the mid-1960s. Prior to the Meredith College
acquisition, the study area was an alfalfa field when it was part of the Tucker
Farm (Johnson 1972, Stenbuck and Waller 2002). The forest extends beyond the
Meredith College property; its east–west axis varies in length from 150 to 400 m
and its north–south axis ranges from 300 to 550 m (Fig.1).
Figure 1. Aerial photo of the study area in Raleigh, NC. The 1-ha plot is located in a fragmented
forest on the Meredith College property (white square; A). Power-lines (white
line; B) are located along the western edge of the research plot (circles represent plot
28 Southeastern Naturalist Vol. 10, No. 1
In the fragmented forest we set up a one-hectare (100- x 100-m) permanent
plot on the north–south and east–west axes (Fig. 2). Power-lines and
maintained grassland were located on the western boundary of the study plot
which defined the forest edge in the study. The power-line right-of-way has a
width of 30 m. Within the study plot, there were ninety 10- x 10-m subplots
marked off with flags from 10 to 100 m from the western boundary or forest
edge, and twenty 10- x 5-m subplots within the first 10 m of this edge. The
edge subplots were located within the first 5 m from the western boundary of
the plot, and the interior subplots were 5–100 m away from the western plot
boundary. The southern boundary of the forest plot was located approximately
20 m from another forest edge. The slope and aspect of the plot were collected
every 40 m throughout the plot using a clinometer and compass, respectively.
Slope had a minimum of 1.5°, maximum of 22.5°, and a mean of 8.2° (n = 12).
For aspect, the minimum was 218°, the maximum was 327°, and the mean was
270° (n = 12).
Power-lines located along the western side of the forest were constructed
in the early 1970s. Progress Energy maintained the vegetation area under the
Figure 2. The grid represents the study plot located on Meredith College’s campus, Raleigh,
NC; line on the western edge represents the power-line. The distance away from
the power-line in meters is located along the northern side of the plot.
2011 A.S. Powell and E.S. Lindquist 29
power-lines by annual mowing until 2007 and applied herbicide (mixture of Accord
®, Arsenal Powerline®, and Milestone®) every three years (Henry Dickens,
pers. comm.). They also pruned tree branches extending into the corridor every
four to five years. During the study, the meadow under the lines was mowed and
the edge cut on 7 November 2007.
We permanently tagged all living trees that had at least one stem with a diameter
at breast height (DBH) ≥ 5 cm in the 1-ha plot with round aluminum
tags on the north side of the trees. DBH was measured at 1.3 m for all stems of
the tree. We collected leaf samples from all the tree species on the plot to create
voucher specimens for the Meredith College herbarium, and indentified all
individuals (E.C. Swab, environmental consultant, Raleigh, NC, pers. comm.;
Swanson 1994). The field research and data collection was conducted August
To determine how species composition changed along the 100-m gradient
from the edge of the forest adjacent to the power-line corridor to the interior
of the forest (Fig. 2), we calculated tree species richness (S) for the twenty
5- x 10-m subplots (0–5 and 5–10 m from the forest edge) and the remaining
ninety 10- x 10-m subplots (10–100 m from the forest edge), and the Shannon-
Weiner diversity index (H) for each of the 10- x 10-m subplots, including the
0- to 10-m subplots. To assess how similar the edge subplots (0–10 m from
edge) were to all other subplots in species composition, we calculated the Sorenson’s
(Ss) similarity index for each of the 0–10 m plots contrasted with each
of the interior subplots. We spatially represented the variation in the forest
community composition with a non-metric multidimensional scaling (NMS)
ordination analysis using PC-ORD software (McCune and Grace 2002). For
the NMS ordination we used a matrix representing the species abundance of
each 10- x 10-m subplot. Before the analyses, we used Beal’s Smoothing to
transform the heterogeneous compositional data due to the high frequency of
zeros (McCune and Grace 2002). For the analysis, we used the Sorenson distance
measure recommended by McCune and Grace (2002) for NMS analysis
of community data. A two-axis representation of the species composition in
subplot space was found to minimize the stress of the model.
We also assessed how our forest structure parameters varied relative to the
100-m gradient in the study plot by calculating the mean DBH (diameter-at-breast
height, cm), stem density (ha-1), and total basal area (m2 ha-1) for the twenty 5- x
10-m subplots (0–5 and 5–10 m from the forest edge) and the remaining ninety 10-
x 10-m subplots (10–100 m from the forest edge).
Prior to testing how the species composition and forest structure parameters
differed among the different subplots grouped by 5-m (0–5 m and 5–10 m for the
forest structure parameters only) or 10-m intervals, we tested each parameter for
normality using the Shapiro-Wilk test (JMP 8.0). All variables, with the exception
of the Shannon-Weiner (H) diversity index, did not fit a normal distribution.
30 Southeastern Naturalist Vol. 10, No. 1
We used the Kruskal-Wallis (JMP 8.0) for all non-normal parameters, and an
analysis of variance (ANOVA; JMP 8.0) for the Shannon-Weiner (H) index.
Tukey-Kramer post-hoc tests (JMP 8.0) were calculated to obtain pair-wise comparisons
for any parameter that showed differences in the mean values across the
distance classes. To determine if mean DBH was related to stem density as we
predicted, we used a linear regression (JMP 8.0). In all statistical tests, the null
hypothesis was rejected if the P-value was ≤ 0.05.
We tagged, identified, and measured 818 trees of 20 species (Table 1). The
largest tree on the plot was a Quercus alba L. (White Oak), which had a DBH
of 86.4 cm. Over 63% of the plot was made up of 3 species: Acer rubrum L.
(Red Maple; 30.6% of stems), Oxydendrum arboreum (L.) DC. (Sourwood;
22.5% of stems), and White Oak (10.5% of stems). There were three species
(Cornus florida L. [Flowering Dogwood], Juniperus virginiana L. [Eastern
Redcedar], and Sassafras albidum (Nutt.) Nees [Sassafras]) that only occurred
once in the plot. The mean DBH for each species ranged from 8.9 ± 3.4 cm
(Nyssa sylvatica Marsh. [Blackgum]) to 34.8 ± 6.8 cm (Pinus echinata P. Mill.
Table 1. Species composition and diameter at breast height (DBH) of a fragmented urban forest
on the Meredith College campus, Raleigh, NC (35°48'22.05"N, 78°41'31.39"W). Over 63%
of the plot is made up of 3 species: Red Maple, Sourwood, and White Oak. For each species,
the sample size (n), minimum (min.), maximum (max.), mean, and standard deviation (SD)
for the DBH are included.
% of Stems DBH (cm)
Common name Scientific name (n = 818) n Min. Max. Mean SD
Red Maple Acer rubrum 30.6 250 2.9 50.4 11.4 8.0
Sourwood Oxydendrum arboreum 22.5 184 3.3 30.0 9.1 3.9
White Oak Quercus alba 10.5 86 4.1 86.4 33.9 16.0
Blackgum Nyssa sylvatica 7.5 61 3.7 19.4 8.9 3.4
Mockernut Hickory Carya tomentosa Nutt. 4.5 37 3.9 32.9 15.1 8.4
Sweetgum Liquidambar styraciflua L. 4.5 37 5.5 31.9 11.0 5.8
Scarlet Oak Quercus coccinea Muenchh. 3.9 32 4.3 55.9 20.5 13.9
Tuliptree Liriodendron tulipifera L. 3.4 28 4.3 59.9 20.8 14.1
American Beech Fagus grandifolia Ehrh. 2.7 22 3.9 44.7 13.0 9.7
Black Oak Quercus velutina Lam. 2.1 17 4.2 47.0 23.0 12.8
Shortleaf Pine Pinus echinata 2.1 17 17.0 43.6 34.8 6.8
Red Oak Quercus rubra L. 1.3 11 8.5 51.7 27.0 15.8
Loblolly Pine Pinus taeda L. 1.2 10 5.6 51.5 32.0 14.9
Southern Red Oak Quercus falcata Michx. 1.1 9 13.5 54.1 31.5 13.6
Pignut Hickory Carya glabra (Mill.) Sweet 0.9 7 13.5 34.2 22.5 8.3
Black Cherry Prunus serotina Ehrh. 0.5 4 5.6 15.5 10.0 4.5
Shagbark Hickory Carya ovata (Mill.) K. Koch 0.4 3 5.7 31.9 16.3 13.8
Flowering Dogwood Cornus florida 0.1 1 5.7 5.7 5.7 -
Eastern Redcedar Juniperus virginiana 0.1 1 9.8 9.8 9.8 -
Sassafras Sassafras albidum 0.1 1 11.1 11.1 11.1 -
2011 A.S. Powell and E.S. Lindquist 31
Figure 3. A. Tree species richness (S) (species/subplot) compared to the distance (m)
from the forest edge of the 1-ha plot. B. Shannon-Weiner (H) compared to the distance
(m) from the forest edge on the plot. C. Sorenson (Ss) index for the 0–10-m subplots (n =
10) contrasted with all remaining subplots (n = 99). The Ss was averaged for all subplots
within any distance (m) from the forest edge category (n = 9 for 0–10 m, and n =10 for
all other distances). For (A), (B), and (C): error bars = ± 1 standard deviation (stdev) (n =
10), and distance treatments which share the same letter are not significantly different
from each other. (P ≤ 0.05).
32 Southeastern Naturalist Vol. 10, No. 1
We found that there was no difference in tree species richness (S) along the
100-m gradient from the forest edge next to the power-line corridor into the interior
of the forest (χ2 = 13.54, P = 0.195; Fig. 3A). Tree species richness ranged
from 3.6 to 5.8 species per subplot. We found that the mean species diversity
(H) of each of the subplot was 1.28 ± 0.39, and the diversity index did not vary
along the distance gradient from the forest edge (F = 1.425, P = 0.199; Fig. 3B).
The calculated Ss between the edge plots (0–10 m) and all other subplots varied
from 0.28 to 0.34, and we found that when we contrasted the Ss of the first 10 m
from the edge (0–10 m) to each of the other distance classes, the Ss did not differ
significantly (Fig. 3C, χ2 = 11.87, P = 0.221). The NMS ordination also showed
that the species composition of the edge subplots (0–10 m) was not different than
all other subplots (Fig. 4). Although the majority of the edge subplots clustered
together in the NMS ordination space, and therefore were similar to each other
in species composition, they also were similar in species composition to a large
number of interior subplots (Fig. 4).
There was no difference in mean DBH across the distances (χ2 = 13.76, P =
0.184; Fig. 5A). We found that there was a significant difference in stem density
(ha-1) across the distances (χ2 = 26.77, P = 0.003; Fig. 5B). The 0–5-m (from the
forest edge) subplots had a higher stem density (0.144 ± 0.0532 stems ha-1) than
all the subplots located 20–100 m from the forest edge (0.066 to 0.104 stems
ha-1), while the 5–20-m subplots had the same stem densities as the 0–5-m and
20–100-m subplots (Fig. 5B). We found that the total basal area for the subplots
within 5 m (0.067 ± 416 m2 ha-1) of the forest edge was smaller than that of the
10–20-m (0.373 ± 1805 m2 ha-1) and 60–70-m (0.381 ± 1253 m2 ha-1) subplots
Figure 4. Non-metric multidimensional scaling (NMS) ordination of species composition
of the one hundred 10- x 10-m subplots. Subplots were grouped into edge (0–10 m from
edge; gray squares) and interior (10–90 m from edge; open circles) categories. Subplots
that are close together in Axes 1 and 2 are similar to each other in species composition.
2011 A.S. Powell and E.S. Lindquist 33
(χ2 = 25.42, P = 0.0046; Fig. 5C). There was a large amount of variability in the
total basal area among the subplots at any given distance (Fig. 5C).
Figure 5. A. Mean DBH (diameter-at-breast height; cm) compared to the distance (m)
from the forest edge of the 1-ha plot. B. Mean stem density (trees/ha) compared to the
distance (m) from the forest edge of the plot. C. Total tree basal area (m2 ha-1) compared
to the distance (m) from the forest edge of the plot. For (A), (B), and (C): error bars = ± 1
standard deviation (stdev) (n = 10), and distance treatments which share the same letter
are not significantly different from each other. (P ≤ 0.05).
34 Southeastern Naturalist Vol. 10, No. 1
We found that as the stem density increased in the subplots, the mean DBH
did not decrease significantly, but a trend was apparent (n =110, r2 = 0.034, P =
0.053; Fig. 6). To investigate this trend further, we made a second regression
model where we excluded a subplot with a mean DBH (38.7 cm, 90–100 m;
Fig. 6) larger than two standard deviations from the mean DBH of all subplots.
With this outlier removed, as stem density increased in the subplots, the mean
DBH decreased (n =109, r2 = 0.036, P = 0.038).
Previous literature has shown that forests generally have higher species richness
and stem densities along their disturbed edges (Fraver 1994, Matlack 1994).
The extent to which these edge effects penetrate the forest interior differed from
site to site. In an assortment of tropical and temperate zone forests, there was a
higher stem density and basal area within 20 m of the forest edge (Murcia 1995).
Other results have shown edge effects to extend 15 m to 5 km, depending on
habitat and taxa (Laurance and Yensen 1991). In order to generalize beyond one
study site, we argue that it is critical to focus on the type of edge when determining
how the forest composition and structure is affected by fragmentation.
Our results show that the placement of power-lines along a fragmented urban
forest affects the forest structure but not species composition. Furthermore,
we found that only the first 5 m of forest differs in structure when compared
to the forest interior (up to 100 m from edge). Our results are contrary to some
previous studies investigating other types of edges, which found species compositional
changes along forest edges (McDonald and Urban 2006), but in
support of Luken et al.’s (1991a, 1991b) findings investigating forests adjacent
to power-lines in a rural landscape. Luken et al. (1991a, 199b) found that there
was no difference in tree species richness and diversity (H) between the forest
edge (<10 m from edge) and interior. The continued mowing or removal by
Figure 6. Linear regression of the mean DBH (diameter-at-breast height; cm) and the stem
density (trees/m2) of each subplot (n = 100) within the 1-ha plot. (r2 = 0.037, P = 0.045).
2011 A.S. Powell and E.S. Lindquist 35
herbicides of vegetation below the power-lines may explain why there was no
difference in species richness relative to the edge in both study sites. Likewise,
species richness has been found to increase with the age of the fragmented
patch (Jacquemyn et al. 2001). In our study, we found that the mean diameterat-
breast height (DBH) did not differ in relation to the distance from the forest
edge. We believe that as the interior of the forest continues to mature, the mean
DBH will be lower along the edge compared to the interior because the edge
trees will not be able to increase significantly in size due to the continued maintenance
of the power-line corridor.
Based on our stem density and basal area findings, edge effects on forest
structure clearly extend 5 m into the forest and may extend up to 20 m away from
the forest edge. We found that stem density was higher in plots along the forest
edge (0–5 m from edge) than in plots in the forest interior (≥20 m from edge).
Because the edge of our study plot was routinely disturbed, smaller stems were
more abundant along the edge. In addition, smaller stems were able to grow along
the edge better because the immature, open canopy allows more sunlight to reach
the ground. Our results are in agreement with Luken et al. (1991b); they found
that routine cutting along the edge of the forest leads to higher stem densities.
Forest edges adjacent to power-line corridors may have a higher stem density
when compared to forest edges adjacent to fields and clear-cuts because of the
continual clearing and trimming of the edge vegetation. Furthermore, forests
along power-line corridors may be affected further into the forests due to the
continual human disturbance.
In contrast to the higher stem density along the forest edge, we found that
total basal area was lower in plots along the forest edge (0–10 m from edge)
than some of the more interior plots (10–20 m and 60–70 m from edge).
Luken et al. (1991a) found that the edge had a higher basal area for saplings
and seedlings (DBH < 10 cm) but not for larger trees (DBH ≥10 cm). We
believe our results may be due to a lower mean DBH (7.48 ± 2.01 cm) in
the edge plots caused by the continual maintenance of the forest edge next
to the power-lines. Now that the mowing treatments have stopped, and the
vegetation under the power-lines will be maintained by herbicidal treatment
allowing woody vegetation to grow, we predict that the basal area of the forest
edge will increase as the trees grow larger.
In addition to edge type, the differences in the extent of edge effects may be
related to forest type, age (Jacquemyn et al. 2001), area and shape (Jacquemyn et
al. 2001, Laurance and Yensen 1991), or orientation (Matlack 1993, Sherich et al.
2007). The smaller and more irregular in shape the fragment is, the stronger the
edge effect may be (Laurance and Yensen 1991). Given that our forest fragment
is small in size (>22 ha) relative to those used in Laurance and Yensen’s (1991)
models (0–500 ha), fairly regular in shape (Fig. 1), approximately 40 years old,
and has a western-facing edge and a north-facing slope, we expect that the edge
effects due to these factors were not as strong as documented in these other studies
(Jacquemyn et al. 2001, Laurance and Yensen 1991, Matlack 1993, Sherich et
36 Southeastern Naturalist Vol. 10, No. 1
al. 2007). Because our forest edge is disturbed on a regular basis for power-line
maintenance, we believe that the changes in abiotic and biotic conditions due to
this regular disturbance override any variations in edge effects due to age, area,
shape or orientation of the forest.
Based on our findings in an urban, fragmented forest in the piedmont of
North Carolina, we conclude that forest structure (stem density and total basal
area) was altered at least 5 m from a routinely disturbed forest edge due to
power-line right-of-way maintenance. However, we found no changes in mean
tree DBH, tree species richness, or diversity relative to distance from the forest
edge. Further research at our study site should be conducted to determine
if the routine maintenance of the forest edge by herbicidal treatments continues
to affect the structure of the forest as it ages. Furthermore, we encourage
additional studies investigating how power-lines affect forest composition and
structure because our results highlight how their maintenance causes the edge
effects to differ from those found adjacent to other types of infrastructure
or causes of forest fragmentation. Beyond the documented effects on forest
structure and composition, we recommend that further research is conducted
under power-lines to investigate how the managed corridors affect the spread
of invasive species, alteration of small mammal habitat, and the dynamics of
herbaceous vegetative communities.
Our findings confirm that power-line right-of-way maintenance can magnify
the ecological effects of forest fragmentation in urban settings. Based on our research
we recommend that, if possible, power companies minimize the placement
of new power-lines in intact forest habitats. This would be beneficial to power
companies given that direct contact between power-lines and trees or tree branches
can cause power outages (Appleton 2006). In addition, managing vegetation
along utility lines costs between two to ten billion dollars in North America (Appleton
2006), with much of this expense due to pruning tree branches. Therefore,
in order to minimize the expense of managing woody vegetation, we recommend
that when possible, power-lines are routed through disturbed grasslands or other
low-lying vegetated areas where tree cutting and pruning is avoided.
We would like to thank the Meredith College Undergraduate Research Committee
for funding and supporting us throughout the project. The publication of this paper was
supported by a grant to Meredith College from the Margaret A. Cargill Foundation. We
would like to thank B. Powell, J. Powell, and L. Racz for their field assistance, and E.C.
Swab for his assistance with tree identification.
Appleton, B.L. 2006. Designing and implementing utility-line arboreta. Arboriculture
and Urban Forestry 32:80–85.
Benítez-López, A., R. Alkemade, and P.A. Verweij. 2010. The impacts of roads and other
infrastructure on mammal and bird populations: A meta-analysis. Biological Conservation
2011 A.S. Powell and E.S. Lindquist 37
Fraver, S. 1994. Vegetation responses along edge-to-interior gradients in the mixed
hardwood forests of the Roanoke River basin, North Carolina. Conservation Biology
Fahrig, L. 2003. Effects of habitat fragmentation on biodiversity. Annual Review of Ecology,
Evolution, and Systematics 34:487–515.
Harper, K.A., S.E. Macdonald, P.J. Burton, J. Chen, K.D. Brosofske, S.C. Saunders,
E.S. Euskirchen, D. Roberts, M.S. Jaiteh, and P. Esseen. 2005. Edge influence on
forest structure and composition in fragmented landscapes. Conservation Biology
Jacquemyn, H., J. Butaye, and M. Hermy. 2001. Forest plant species richness in small,
fragmented mixed deciduous forest patches: The role or area, time, and dispersal
limitation. Journal of Biogeography 28:801–812.
Johnson, M.L. 1972. A History of Meredith College, 2nd Edition. Edwards and Broughton
Company, Raleigh, NC.
Johnstone, R.A. 1990. Vegetation management: Mowing to spraying. Journal of Arboriculture
Laurance, W.F., and E.Yensen. 1991. Predicting the impacts of edge effects in fragmented
habitats. Biological Conservation 55:77–92.
Laurance, W.F., M. Goosem, and S.G.W. Laurance. 2009. Impacts of roads and linear
clearings on tropical forests. Trends in Ecology and Evolution 24:659–669.
Luken, J.O., A.C. Hinton, and D.G. Baker. 1991a. Forest edges associated with powerline
corridors and implications for corridor sitting. Landscape and Urban Planning
Luken, J.O., A.C. Hinton, and D.G. Baker. 1991b. Assessment of frequent cutting as
a plant-community management technique in power-line corridors. Environmental
Luken, J.O., A.C. Hinton, and D.G. Baker. 1992. Response of woody plant communities
in power-line corridors to frequent anthropogenic disturbance. Ecological Applications
Matlack, G.R. 1993. Microenvironment variation within and among forest edge sites in
the eastern United States. Biological Conservation 66:185–194.
Matlack, G.R. 1994. Vegetation dynamics of the forest edge: Trends in space and successional
time. Journal of Ecology 82:113–123.
McCune, B., and J.B. Grace. 2002. Analysis of Ecological Communities. MjM Software
Design, Gleneden Beach, OR.
McDonald, R.I., and D.L. Urban. 2004. Forest edges and tree growth rates in the North
Carolina piedmont. Ecology 85:2258–2265.
McDonald, R.I., and D.L. Urban. 2006. Edge effects on species compositions and
exotic species abundance in the North Carolina piedmont. Biological Invasions
Murcia, C. 1995. Edge effects in fragments forests: Implications for conservation. Tree
Pohlman, C.L., S.M. Turton, and M. Goosem. 2009. Temporal variation in microclimatic
edge effects near powerlines, highways, and streams in Australian tropical rainforest.
Agricultural and Forest Meteorology 149:84–95.
Ries, L., R.J. Fletcher, Jr., J. Battin, and T.D. Sisk. 2004. Ecological responses to habitat
edges: Mechanisms, models, and variability explained. Annual Review of Ecology,
Evolution, and Systematics 35:491–522.
38 Southeastern Naturalist Vol. 10, No. 1
Riitters, K.H., J.D. Wickham, R.V. O’Neill, K.B. Jones, E.R. Smith, J.W. Coulston, T.G.
Wade, and J.H. Smith. 2002. Fragmentation of continental United States forests. Ecosystems
Sherich, K., A. Pocewicz, and P. Morgan. 2007. Canopy characteristics and growth rates
of Ponderosa Pine and Douglas Fir at long-established forest edges. Canadian Journal
of Forest Research 37:2096–2105.
Stenbuck, R., and T. Waller. 2002. Meredith Traditions and History: Land-Use History of
Meredith College, Meredith College Press, Raleigh, NC.
Swanson, R.E. 1994. A Field Guide to the Trees and Shrubs of the Southern Appalachians.
John Hopkins University Press, Baltimore, MD. 399 pp.
Williams-Linera, G. 1990. Vegetation structure and environmental conditions of forest
edges in Panama. Journal of Ecology 78:356–373.