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22001155 NORTHEASTERN NATURALIST 2V2(o2l). :2224,8 N–2o6. 12
Response of Japanese Barberry to Varying Degrees of
Defoliation
Dirk Vanderklein1,*, Anthony Cullen1, and Jean-Edson Belcourt1
Abstract - Until recently, it was thought that Berberis thunbergii (Japanese Barberry), a
non-native invasive plant that has become particularly widespread in certain regions of
New Jersey, benefited from a lack of herbivorous defoliators. However, in 2007 extensive
defoliation was documented across a wide geographical distribution in New Jersey, calling
this assumption into question. We tested whether Japanese Barberry was negatively affected
by partial defoliation by manually clipping 50% or 100% of leaves on current-year stems
on small and large plants in the summer of 2008. We found almost no impact of defoliation
on growth, carbon storage, or leaf-level physiology for either treatment. We noted some
differences between large and small plants, but these were not related to defoliation treatments.
Our results suggest that, even in the presence of herbivory, Japanese Barberry is
capable of maintaining growth and carbon reserves, thus making it an effective competitor
for resources.
Introduction
Invasive plants are estimated to cost the US economy ~$26 billion dollars a year
in damage to agriculture (Pimentel et al. 2000). In addition, they pose a serious
threat to native vegetation, and by extension to native ecosystems, by displacing local
flora and fauna (Pimentel et al. 2000) and by altering nutrient cycles (Ehrenfeld
et al. 2001) and fire cycles (Brooks et al. 2004). In New Jersey, invasive plants have
been identified as one of the top 4 ecological threats in the state (Snyder and Kaufman
2004). New Jersey is home to a very large number of indigenous and locally unique
plant species, but 1/3 of all plant species in the flora are non-native (Snyder and
Kaufman 2004). While not all non-native plant species are invasive, a number have
proven to be so, including Berberis thunbergii DC. (Japanese Barberry).
The enemy-release hypothesis (ERH; Keane and Crawley 2002) predicts that
one reason non-native plants can become invasive is that they grow without their
natural predators (herbivores), and therefore, have an advantage over native species
that are subject to loss of foliage through herbivory and the need for additional
productivity to replace lost foliage. However, several studies have shown that under
controlled conditions non-native invasive plants may experience just as much
herbivory as co-occurring native species (Agrawal and Kotanen 2003, Ashton and
Lerdau 2008). Alternatively, the evolution of increased competitive ability (EICA)
hypothesis introduced by Blossey and Nötzold (1995) proposes that non-native
plants have a growth advantage over native plants because they don’t have to
invest energy into defensive compounds and can therefore allocate their energy into
1Department of Biology and Molecular Biology, Montclair State University, Montclair, NJ.
*Corresponding author - vanderkleid@mail.montclair.edu.
Manuscript Editor: Howard S. Ginsberg
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growth. However, this means then, that these plants should be more susceptible to
a novel defoliator and possible loss of growth as a result. A third possibility is that
invasive plants may not be negatively affected by defoliation as a result of low investment
in leaf tissue (Leishman et al. 2007, Xu et al. 2007). Determining whether
native or non-native invasive defoliated plants are at a disadvantage is further complicated
by the fact that most plants are known to compensate for loss of leaf area
with higher photosynthetic rates such that there may be no net decrease in growth or
reproduction (Trumble et al. 1993, Vanderklein and Reich 1999). However, not all
plants show compensation (Vanderklein et al. 2000); thus, the impact of defoliation
on the competitive ability of invasive plants should depend on the extent to which
growth and energy reserves are affected by defoliation.
While extensive research has been conducted on the compensatory responses of
plants to herbivory in general (Trumble et al. 1993), very little research appears to
exist with regard to invasive plants and their responses to defoliation. Pratt et al.
(2005) reported that the invasive tree Melaleuca quinquenervia (Cav.) S.T. Blake
(Australian Paperbark) maintained foliage biomass and increased stem growth, but
had reduced fruit production in response to partial defoliation. Similarly, Schierenbeck
et al. (1994) found that the invasive Lonicera japonica Thunb. (Japanese
Honeysuckle) received less herbivore damage and showed greater growth compensation
than its native congener L. sempervirens L. (Trumpet Honeysuckle). Thus,
defoliation may not affect invasive plants enough to have an impact on their ability
to remain invasive and outcompete native plants.
Ehrenfeld (2009) noted that in 2007 the native moth Coryphista meadii (Packard)
(Barberry Geometer Moth) caused extensive defoliation of current-year stems
of Japanese Barberry. This was the first report of extensive defoliation on Japanese
Barberry and it led to the speculation that these plants would be negatively impacted
(Ehrenfeld 2009). The goal of our study was to test to what extent herbivory reduced
growth or energy reserves of Japanese Barberry by artificially defoliating the current
leaves of large and small plants. We divided plants into 2 size classes because
Ehrenfeld (2009) had noted that smaller plants exhibited less evidence of herbivory
than larger plants. We hypothesized that energy reserves but not growth of defoliated
plants would be lower. We also hypothesized that because of their reduced
energy reserves, the small plants would be more strongly affected by defoliation
than large plants.
Field-site Description
In early spring 2008, we established 2 plots at Jockey Hollow (40º45'45.82''N,
74º32'33.58''W), in Morristown National Historical Park, located near Morristown,
NJ. Both plots were located in the understory of mature broad-leaved trees of several
species typical of Acer saccharum Marsh. (Sugar Maple)–mixed hardwood
forests in New Jersey (Collins and Anderson 1994). The first plot was located within
an Odocoileus virginianus (Zimmermann) (White-tailed Deer) exclosure from
which invasive plants had been removed several years earlier. Japanese Barberry
plants inside the exclosure were fairly small—about 0.3 m tall, with less than 3 stems/plant.
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The second plot was located adjacent to the exclosure and contained much larger
plants—about 1 m tall, with 10–20 stems per plant. Deer browse was non-existent
for both groups of plants, and all plants were within 10 m of e ach other.
Methods and Materials
Study design
We categorized all Japanese Barberry plants within a pre-determined measurement
area as either small or large and chose 45 plants from each group for inclusion
in the study. We randomly selected 15 plants from each size class for each of 2
defoliation treatments, and 15 for no defoliation (controls). During the third week
of June 2008, when all leaves had fully matured, we manually applied defoliation
treatments by cutting half (“50% defoliation” treatment) or all (“100% defoliation”
treatment) leaves from all current-year shoots of each branch. We completed
defoliation treatments within a week. Although our defoliation treatment did not
mimic the typical defoliation pattern of the Barberry Geometer Moth, we chose
this method in order to have as big an impact on the starch reserves as possible,
thus yielding a result similar to what we would expect as a result of a later defoliation
event as compared to an earlier one (Reich et al. 1993). We chose to remove
leaves only from current-year stems because that closely mimicked what had been
observed following defoliation by Barberry Geometer Moth the previous year (Ehrenfeld
2009). We collected all clipped leaf parts from each plant to determine total
leaf biomass for the season.
Measurements
Physiology. Just after each biomass harvest in mid-July and mid-September, we
randomly selected 5 plants from each size class and defoliation treatment to measure
photosynthesis (Pn), transpiration (E), and stomatal conductance (g) using an
LI6400 infrared gas analyzer (LiCor Ltd., Lincoln, NE). We made all measurements
with the light intensity set at 1000 μmol/m2/s to compare plants at their maximum
rates. Instantaneous water-use efficiency (WUE) was calculated as the ratio of photosynthesis
to transpiration. Additionally, we measured leaf water-potential (LWP)
using a pressure chamber (PMS Inc. Albany, OR). All measurements took place
between 10 AM and 12 PM when we assumed that all plants would be at maximal
(Pn, E, g) or minimal (LWP) natural potential levels. Furthermore, we assumed that
because all plants measured were within 10 m of each other, soil water-potential
would be the same for all plants. Japanese Barberry leaves are relatively small and
they did not fully cover the gas-analyzer chamber. Therefore, rates of photosynthesis,
transpiration, and stomatal conductance were corrected for leaf area after
we measured total leaf area enclosed in the chamber at each measurement. We
determined leaf area with a portable leaf-area scanner (CID 202, CID Bioscience,
Camas, WA).
Starch and biomass. At the end of March but still during the dormant season,
we harvested 10 plants per size class and defoliation treatment before any new
growth had occurred. We refer to this as harvest 1 (H1). We divided these plants
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into roots (R) and stems (S). We tried to harvest all roots of each plant by digging
well around each plant before removing it from the soil; however, it is likely that a
small fraction of the fine roots were lost in the process. At the time of harvest, we
put harvested plant sections in a cooler with ice, transferred them to paper bags
at the lab, and dried the samples at 50 °C using a forced-air drying oven for several
days until they were fully dried. In late July and early August, we harvested
a second group of small and large plants from all defoliation treatments—harvest
2 (H2). For the second harvest, we divided each plant into roots (R), non-current
stem (OS), current stem (NS), regrowth stem (RS), leaves on non-current stem
(OL), leaves on current stem (NL), leaves on regrowth stem (RL), and fruit (FRT).
Regrowth refers to stems and leaves that appeared after defoliation treatments
were applied. Field treatment and drying protocols were the same as for H1. We
analyzed these plants to determine biomass and starch content. We also calculated
leaf-mass per unit area (LMA) for each harvested plant by collecting a sub-sample
of leaves, measuring their dry mass, and dividing this value by the sample’s leaf
area. After all plant parts had been dried and weighed, we ground the samples
to a fine powder in a Wiley mill to pass through a #40 mesh (0.5mm; Thomas
Scientific, Swedesboro, NJ). Following grinding, we used an enzymatic and
colorimetric method to analyze starch content of each sample. The basic procedure
was a modification of the method described by Haissig and Dickson (1979).
We extracted soluble sugars and pigments with 80% ethanol heated to 80 °C by
placing samples in the hot ethanol for 5 min, after which we centrifuged them and
decanted the liquid from each sample tube. We repeated this procedure until the
warmed ethanol remained clear, then dried samples in a forced-air drying oven at
50 ºC overnight. We hydrated the dry samples with a buffer solution and boiled
them for 15 minutes, added an enzyme solution of amyloglucosidase (15 U/ml)
to the cooled samples, and incubated them at 50 ºC for 24 h. After incubation, we
removed an aliquot from each sample. In addition, we set up a series of glucose
standards. Both the aliquot samples and the glucose standards were combined
with a color-reagent, heated to 37 ºC for 30 min, and then read at 450 nm using
a spectrophotometer (Genesys 20; Thermo Scientific, Waltham, MA) measuring
absorbance. We used the standard curve derived with the glucose standards to determine
the starch content of each sample.
Analysis
We employed 2 types of statistical analyses. First, we ran a factorial ANOVA
(JMP 10, SAS Institute, Cary, NC) to test effects of various defoliation treatments,
plant size, harvest date, and plant part on the variables measured. If we noted a
significant difference, we assessed differences between means with Tukey-Kramer
HSD comparisons; differences between means were considered significant if P less than
0.05. Because there were very few significant treatment effects (size, harvest, defoliation)
among plant parts, we lumped data into specific categories (e.g., harvest)
for each specific comparison to allow the largest sample size possible. We used
ANOVA to test differences between these specific mean responses and indicated
significant differences by providing a specific P-value.
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Results
Starch
Defoliation treatment had no effect on starch content for any combination of
plant size or defoliation treatment (Table 1). However, we observed significant effects
of plant part, harvest date, and plant size on starch content. At the end of the
summer (H2), differences in starch allocation between non-current, current, and
regrowth plant parts depended on the plant part. Roots (R) had the highest starch
content followed by OS, RS, and RL; NS were intermediate; and NL and OL leaves
had the least starch (Fig. 1). Starch content of large and small control-plant roots
was similar between harvest dates (Fig. 2), but starch content of stems increased
significantly between harvest dates for both large and small control plants (Fig. 2).
Plant size did not affect starch concentration, except that in H1 plants, large-plant
stems had higher starch concentrations than small-plant stems (Fig. 2). For the first
harvest, root-starch content was higher than stem-starch content (all parts combined
; data not shown). For the second harvest, root-starch content was greater
than stem-starch content (all parts combined), which was significantly higher than
Figure 1. Starch content (mean ± SE) of plant sections after the second harvest. Plant sections
are defined as follows: NL = leaves on current stem, OL = leaves on non-current stem,
RL = leaves on regrowth stem, R = roots, NS = current stem, OS = non-current stem, and
RS = regrowth stem. Numbers indicate significant differences between plant sections.
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leaf-starch content regardless of plant size (F = 102.7796, df = 2,170; P < 0.001;
Fig. 3).
Biomass
Defoliation significantly reduced the NL biomass of large plants (F = 11.8022;
df = 2, 12; P = 0.0015), but not small plants (F = 0.8354; df = 2, 8; P = 0.4683)
(Table 2). Average leaf area for defoliated small plants was also not significantly
different from controls (data not shown). This result suggests that the small plants
were either not defoliated as completely as planned or that the leaves increased in
size following defoliation. For all other plant parts, regardless of plant size, there
was no effect of defoliation on total biomass, root-to-shoot ratio, or LMA (Table 3).
LMA for large plants was consistently higher than for small plants regardless of leaf
type (OL: F = 27.8175; df = 1, 26; P < 0.001; NL: F = 19.2154; df = 1, 17; P = 0.001;
RL: F = 19.0071; df = 1, 18; P = less than 0.001; Fig. 4). Average mass-per-plant-section
was consistently and significantly higher for large plants than small plants; thus, total
plant mass was greater for large plants than small plants (F = 35.7877; df = 1, 31;
Figure 2. Starch content (mean ± SE) of roots and stems (all sections combined) of control
plants by plant size and harvest date. Numbers indicate significant differences (P < 0.05)
between plant sizes within plant part and harvest. Letters indicate significant differences
(P ≤ 0.05) between harvest dates within plant size and part.
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Table 2. Biomass of plant parts in response to defoliation treatments and plant size. Results presented include mean ± SE (sample size). L = large plants, S
= small plants, R = roots, OS = non-current stem, NS = current stem, RS = regrowth stem, OL = leaves on non-current stem, NL = leaves on current stem,
and RL = leaves on regrowth stem. Letters indicate significant differences between treatments within a plant size. [WHAT DOES ASTERISK SIGNIFY?]
Treatment Size R (g) OS (g) NS (g) RS (g) OL (g) NL (g) RL (g)
0 L 165.68 ± 33.64 (5) 717.32 ± 363.60 (5) 45.22 ± 7.96 (5) 2.33 ± 1.49 (4) 73.30 ± 18.83 (5) 23.06 ± 4.50A (5) 0.84 ± 0.49 (4)
0 S 3.83 ± 0.92* (5) 5.52 ± 1.44 (5) 2.87 ± 2.00 (5) 0.29 ± 0.11(2) 1.71 ± 0.58 (5) 1.63 ± 0.76 (4) 0.32 (1)
50 L 197.92 ± 30.90 (5) 781.02 ± 108.63 (5) 60.86 ± 12.14 (5) 7.52 ± 2.70(3) 107.08 ± 12.94 (5) 14.91 ± 3.23B (5) 2.01 ± 0.73 (3)
50 S 7.15 ± 1.86* (5) 9.92 ± 3.40* (4) 5.66 ± 1.57 (5) 0.35 ± 0.19(4) 5.07 ± 1.49 (4) 1.02 ± 0.24 (5) 0.66 (1)
100 L 139.53 ± 34.04 (5) 550.44 ± 141.74 (5) 35.71 ± 8.91 (5) 3.48 ± 1.39(5) 77.23 ± 12.08 (5) 1.18 ± 0.61C (5) 1.17 ± 0.75 (5)
100 S 4.44 ± 0.73* (6) 6.37 ± 1.17 (6) 1.89 ± 1.02 (6) 0.17 ± 0.02(3) 2.75 ± 0.44 (5) 0.54 ± 0.33 (2)
Table 1. Starch content of plant parts by harvest date and treatment (Trmnt). Results presented include mean ± SE (sample size). R = roots, OS = noncurrent
stem, NS = current stem, RS = regrowth stem, OL = leaves on non-current stem, NL = leaves on current stem, RL = leaves on regrowth stem, and
NDA = no data available. Letters indicate significant differences between harvest dates; see Fig. 1 for additional statistics.
Date Trtmnt Size R (mg/g) OS (mg/g) NS (mg/g) RS (mg/g) OL (mg/g) NL (mg/g) RL (mg/g)
1 C L 77.89 ± 3.20A (17) 20.52 ± 2.10A (20)
1 C S 66.85 ± 4.42 (20) 10.65 ± 1.14A (20)
2 C L 83.84 ± 8.92B (3) 53.68 ± 5.46B (8) 41.14 ± 15.49 (5) 46.03 ± 21.64 (4) 13.65 ± 2.77 (5) 8.28 ± 4.09 (5) 22.60 ± 4.86 (4)
2 C S 77.07 ± 3.24 (5) 52.44 ± 1.71B (5) 31.31 ± 5.58 (4) 25.57 (1) 15.25 ± 8.54 (5) 13.86 ± 8.89 (3) 18.69 (1)
2 50 L 92.42 ± 2.74 (5) 50.88 ± 5.64 (5) 27.67 ± 5.23 (4) 29.75 ± 17.50 (3) 11.91 ± 2.86 (6) 19.06 ± 7.25 (6) 38.70 ± 20.42 (2)
2 50 S 67.63 ± 15.02 (5) 61.30 ± 5.66 (5) 20.88 ± 9.23 (5) 3.49 (1) 10.80 ± 3.69 (5) 14.72 ± 1.50 (5) 12.20 (1)
2 100 L 84.58 ± 4.59 (5) 62.60 ± 7.43 (5) 25.49 ± 5.39 (5) 40.89 ± 16.84 (5) 11.16 ± 3.80 (5) 32.08 ± 16.74 (4) 43.12 ± 15.33 (3)
2 100 S 75.70 ± 3.73 (6) 56.48 ± 4.82 (6) 20.40 ± 3.10 (6) NDA 9.58 ± 2.64 (6) NDA 14.81 (1)
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P < 0.001; data not shown). Within large plants, OS stems had significantly more
mass than all other plant parts (F = 23.5175; df = 7, 105; P < 0.001). Within small
plants, OS and roots had significantly greater mass than NL and RS (F = 8.4640;
df = 5, 75; P < 0.001; Table 2). Current stems (NS) and OL were intermediate in
mass to these plant sections (regrowth leaves were not included in the analysis due
to insufficient sample size). Another significant difference between large and small
plants is that large plants had fruits (average mass = 12.22 ± 2.16 g) and small plants
had none (Table 3) . There was no significant difference between small and large
plant root-to-shoot ratios (Table 3).
Physiology
Defoliation had essentially no effect on leaf water-potential, net photosynthesis,
stomatal conductance, transpiration, or water-use efficiency for all sections of
leaves measured. The only effect noted was for leaves on RL stems where transpiration
increased for partially defoliated plants relative to control plants (F = 4.2483;
df = 2, 28; P = 0.0245; data not shown). Size and time of harvest had a significant
Figure 3. Starch content (mean ± SE) of roots, leaves, and stems of large and small plants after
the second harvest. Numbers indicate significant (P ≤ 0.05) differences between plant parts.
Letters indicate significant differences (P ≤ 0.05) between plant sizes within a plant part.
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effect on leaf physiology for all leaf sections and defoliation treatments combined
(Table 4). For large plants, leaf water-potential (F = 22.1494; df = 1, 45; P less than 0.001,)
and water-use efficiency (F = 34.1580; df = 1, 45; P < 0.001) increased, and net
photosynthesis (F = 88.5640; df = 1, 45; P < 0.001), stomatal conductance (F =
13.9428; df = 1, 45; P < 0.001), and transpiration (F = 107.5713; df = 1, 45; P less than
0.001) decreased between the first and second measurement dates (Table 4). For
small plants, net photosynthesis (F = 17.2739; df = 1, 44; P < 0.001) and transpiration
(F = 26.0351; df = 1, 37; P < 0.001) also decreased between measurement
dates. Leaf water-potential (F=0.2045; df = 1, 45; P = 0.6533) and stomatal conductance
(F = 0.0799; df = 1, 44; P = 0.7788) were unchanged, but water-use efficiency
increased (F = 10.2705; df = 1, 37; P = 0.0028) (Table 4). Stomatal conductance was
consistently lower (Date 1: F = 5.3836; df = 1, 61; P = 0.0237; Date 2: F = 34.7753;
df = 1, 28; P < 0.001), but net photosynthesis (Date 1: F = 29.7236; df = 1, 61; P less than
0.001; Date 2: F = 5.1979; df = 1, 28; P = 0.0304) and water-use efficiency (Date
1: F = 65.4336; df = 1, 54; P < 0.001; Date 2: F = 17.0389; df = 1, 28; P < 0.001)
Figure 4. Leaf mass per area (LMA) for different leaf sections and plant sizes. Plant sections
are defined as follows: NL = leaves on current stem, OL = leaves on non-current stem, and
RL = leaves on regrowth stem. Letters indicate significant differences (P ≤ 0.05) between
plant sizes within a leaf section.
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Table 4. Effect of plant size and date on leaf physiology. Results presented for all leaf sections and defoliation treatments combined and include mean ±
SE (sample size). See Methods section for measurement dates; L = large plants, S = small plants, LWP = leaf water-potential, Pn = net photosynthesis, gs =
stomatal conductance, E = transpiration, and WUE = instantaneous water-use efficiency. Letters indicate significant differences between plant sizes within
a measurement date and symbols (dagger and asterisk) indicate s ignificant differences between measurement dates within plant size.
Date Size LWP (MPa) Pn (μmol/m2/s) gs (mol/m2/s) E (mmol/m2/s) WUE (μmol /mmol)
H1 L -1.36 ± 0.09A* (31) 11.69 ± 0.38A* (31) 0.17 ± 0.01A* (31) 4.52 ± 0.21* (31) 2.73 ± 0.11A* (31)
H1 S -0.92 ± 0.04B (33) 7.90 ± 0.49B* (32) 0.22 ± 0.03B (32) 5.52 ± 0.40* (25) 1.50 ± 0.11B* (25)
H2 L -0.67 ± 0.12A† (16) 5.57 ± 0.53A† (16) 0.09 ± 0.02A† (16) 0.79 ± 0.29A† (16) 13.42 ± 1.49A† (16)
H2 S -0.95 ± 0.07B (14) 4.20 ± 0.71B† (14) 0.21 ± 0.05B (14) 2.01 ± 0.52B† (15) 2.10 ± 0.14B† (15)
Table 3. Biomass of plant parts in response to defoliation treatments and plant size. Results presented include mean ± SE (sample size). Treatment = percent
foliage removed, L = large plants, S = small plants, FRT = fruit mass, TOTAL (-FRT) = total plant mass not including fruit mass, RT/SHT = root- to
shoot-mass ratio, OL = leaves on non-current stem, NL = leaves on current stem, and RL = leaves on regrowth stem. Letters indicate significant differences
between plant sizes within a treatment. LMA = leaf mass per unit area.
Treatment Size FRT (g) TOTAL (-FRT) (g) RT/SHT (g/g) LMA OL (g/m2) LMA NL (g/m2) LMA RL (g/m2)
0 L 10.10 ± 3.24 (5) 1027.12 ± 414.22 (5) 0.28 ± 0.08 (5) 53.27 ± 3.47A (4) 49.61±3.04A (5) 43.74 ± 3.37A (4)
0 S 15.40 ± 5.61 (5) 0.39 ± 0.04 (5) 43.84 ± 1.05B (5) 38.45 ± 1.86B (5) 34.99 ± 1.04B (2)
50 L 14.80 ± 3.64 (4) 833.93 ± 156.03 (7) 0.49 ± 0.17 (5) 55.25 ± 2.43A (5) 58.25 ± 5.83A (4) 45.06 ± 3.07A (3)
50 S 26.23 ± 8.11 (5) 0.50 ± 0.17 (5) 46.87 ± 3.09B (4) 39.19 ± 1.84B (5) 32.55 ± 2.16B (4)
100 L 12.28 ± 4.63 (5) 808.73 ± 191.37 (5) 0.21 ± 0.01 (5) 53.65 ± 2.61A (4) 39.09±2.24A (4)
100 S 15.26 ± 2.44 (6) 0.41 ± 0.02 (6) 44.57 ± 1.14B (6) 29.83 ± 3.50B (3)
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for large plants were consistently higher than for small plants across measurement
dates (Table 4). However, as a result of the fluctuating leaf water-potentials
between measurement dates, leaf water-potential was lower for larger plants at the
first measurement date (F = 16.1112; df = 1, 62, P = 0.001) but higher at the second
measurement date (F = 13.5328; df = 1, 28; P = 0.001) when compared to that of
smaller plants (Table 4). Transpiration rates for large and small plants did not differ
at the first measurement date (F = 3.6414; df = 1, 54; P = 0.0617), but were greater
for small plants (F = 35.1169; df = 1, 28; P < 0.001) than large plants at the second
measurement date (Table 4).
Discussion
Defoliation had virtually no effect on growth, physiology, or carbon storage of
large or small Japanese Barberry plants (Figs. 1–4, Table 4). Thus, we reject both
of our hypotheses. Stomatal conductance and transpiration were higher in regrowth
leaves (RL) compared to non-current leaves (OL) of the greater defoliation treatment
plants (data not shown), but the impact on the plants was negligible given that
neither photosynthesis (Table 4), starch concentration (Fig. 1), nor biomass were
affected (Tables 2, 3). This finding is somewhat surprising given that many plants
show some kind of compensatory response to defoliation (Trumble et al. 1993). By
comparison, Pratt et al. (2005) found compensatory growth in defoliated Australia
Paperbark, which is an invasive woody plant in Florida. Our results suggest that
the amount of leaf loss was not significant enough to cause any adverse effects to
the plant or to trigger a compensatory response. For the larger plants, this lack of
response may be the result of the leaves having a relatively low carbon investment
(LMA; cf Reich et al. 1997, 1999; Fig. 4, Table 3) and the remaining leaves having
a relatively high rate of photosynthesis (at least early in the season) (Table 4)
resulting in a relatively low carbon loss per carbon return. Xu et al. (2007) came
to a similar conclusion regarding the ability of Japanese Barberry to successfully
compete against co-occurring native shrub species under non-defoliated conditions.
Furthermore, low LMA (or high SLA) is commonly associated with invasive
plants and has been shown to be part of a suite of traits that confer an advantage
on non-native plants (Leishman et al. 2007). For the smaller plants, it appears that
compensation occurred in the form of increased leaf size following defoliation;
their average LMA was lower than those of the larger plants (Fig. 4) and many other
species (Reich et al. 1997, 1999) suggesting that these leaves are relatively cheap
to construct. Therefore, it is possible that the leaves of small Japanese Barberry
plants could increase in size without requiring a significant change in carbon input
(photosynthesis) or storage (starch content). The increase in leaf size would have
allowed for greater total carbon gain without increasing the rate of photosynthesis.
Even though small plants had lower rates of photosynthesis than the larger plants,
increased total photosynthesis as a result of increased leaf size would have helped
to compensate for the initial loss of leaf material.
Size also did not appear to play much of a role in the overall physiology and
growth of the plants. As we expected, large plants had greater biomass than small
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D. Vanderklein, A. Cullen, and J.-E. Belcourt
2015
259
plants (Tables 2, 3), but starch concentrations did not differ between the size classes
(Figs. 2, 3). Furthermore, plants in both size classes increased only their stemstarch
concentrations throughout the summer (Fig. 2). Interestingly, large plants
had higher leaf water-potentials and rates of photosynthesis and lower rates of stomatal
conductance and transpiration than small plants at the end of the summer (H2;
Table 1). Consequently, large plants were more water-use efficient than the small
plants at the end of the summer (Table 1). This finding suggests that should water
availability become more limiting for plants in certain areas as a result of global
climate change (Karl 2009), larger Japanese Barberry plants would be expected to
have higher chances of survival, potentially making them even more invasive in
these locations.
Given that Japanese Barberry is generally acknowledged to be a successful invasive
plant species (Ehrenfeld 1997, Silander and Klepeis 1999), our goal here was
not to consider its ability to compete against other species, but to consider the physiological
features that could allow it to be competitive, particularly in response to
defoliation. Taken together, the defoliation, physiological, and growth data suggest
that Japanese Barberry is very well adapted to succeed in the forests of eastern North
America. Earlier work by Ehrenfeld and others on the ability of Japanese Barberry
to enhance soil-nitrogen availability and on its population dynamics provide further
support of this conclusion (Ehrenfeld 1999, Kourtev et al 1999). As Gurevitch et al.
(2013) have pointed out, many suggestions have been made regarding the factors
that enable a species to succeed under novel conditions and potentially become invasive.
Plants may be pre-adapted to succeed (Schlaepfer et al. 2009), they may not be
constrained by the same metabolic tradeoffs (Daehler 2003, Heberling and Fridley
2013, Leishman et al. 2007), or they may not be susceptible to local herbivores in the
same way that native vegetation is, either because they are not approached by local
herbivores or because they have an increased ability to resist or tolerate herbivory
(Agrawal and Kotanen 2003, Ashton and Lerdau 2008, Stastny et al. 2005). Certainly,
it seems likely that non-native plants are idiosyncratic in their abilities to succeed in
novel conditions (Moles et al. 2012). In this case, even though none of the enemies
of Japanese Barberry from its natural range were present at our site, the plants were
apparently not stressed when defoliated. Whether this trait contributes to its invasiveness
or not, it certainly should contribute to its ability to compete successfully with
other vegetation in both its native and non-native range.
Acknowledgments
This paper would not have been possible without collaboration with the late Dr. Joan
Ehrenfeld. She proposed the initial question and identified the field site for our study. It is
our great regret she did not see the final results of her work. Valuable field assistance was
provided by Hyun Kho, Ian Vanderklein, Kim Vanderklein, and Marshall Akita. Anthony
Cullen received funding support from the Montclair State University College of Science and
Mathematics Interdisciplinary Council and the Investors Savings Bank Charitable Foundation.
Jean-Edson Belcourt received funding support from the MARC U-STAR Program
(National Institute of General Medical Sciences #T34GM079079 to Dr. Reginald Halaby).
Northeastern Naturalist
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D. Vanderklein, A. Cullen, and J.-E. Belcourt
2015 Vol. 22, No. 2
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