Northeastern Naturalist 248 D. Vanderklein, A. Cullen, and J.-E. Belcourt 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 Northeastern Naturalist Vol. 22, No. 2 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 249 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. Northeastern Naturalist 250 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 Vol. 22, No. 2 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 Northeastern Naturalist Vol. 22, No. 2 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 251 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. Northeastern Naturalist 252 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 Vol. 22, No. 2 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. Northeastern Naturalist Vol. 22, No. 2 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 253 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. Northeastern Naturalist 254 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 Vol. 22, No. 2 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) Northeastern Naturalist Vol. 22, No. 2 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 255 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. Northeastern Naturalist 256 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 Vol. 22, No. 2 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. Northeastern Naturalist Vol. 22, No. 2 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 257 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) Northeastern Naturalist 258 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 Vol. 22, No. 2 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 Northeastern Naturalist Vol. 22, No. 2 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 260 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 Vol. 22, No. 2 Literature Cited Agrawal, A.A., and P.M. Kotanen. 2003. Herbivores and success of exotic plants: A phyologenetically controlled experiment. Ecology Letters 6:712–715 . Ashton, I.W., and M.T. Lerdau. 2008. Tolerance to herbivory, and not resistance, may explain differential success of invasive, naturalized, and native North American temperate vines. Diversity and Distributions 14:169–178. Blossey, B., and R. Nötzold. 1995. Evolution of increased competitive ability in invasive nonindigenous plants: A hypothesis. Journal of Ecology 83:887–889. Brooks, M.L., C.M. D’Antonio, D.M. Richardson, J.B. Grace, J.E. Keeley, J.M. DiTomaso, R.J. Hobbs, M. Pellant, and D. Pyke. 2004. Effects of invasive alien plants on fire regimes. BioScience 54:677–688. Collins, B.R., and K.H. Anderson. 1994. Plant Communities of New Jersey: A Study in Landscape Diversity. Rutgers University Press, New Brunswick, NJ. 287 pp. Daehler, C.C. 2003. Performance comparisons of co-occuring native and alien invasive plants: Implications for conservation and restoration. Annual Review of Ecology, Evolution, and Systematics 34:183–211. Ehrenfeld, J.G. 1997. Invasion of deciduous forest preserves in the New York metropolitan region by Japanese Barberry (Berberis thunbergii DC.). Journal of the Torrey Botanical Society 124:210–215. Ehrenfeld, J.G. 1999. Structure and dynamics of populations of Japanese Barberry (Berberis thunbergii DC.) in deciduous forests of New Jersey. Biological Invasions 1:203–213. Ehrenfeld, J.G. 2009. Extensive defoliation of Japanese Barberry (Berberis thunbergii DC.) in New Jersey by a native moth, Coryphista meadii. Natural Areas Journal 29:57–63. Ehrenfeld, J.G., P. Kourtev, and W. Huang. 2001. Changes in soil functions following invasions of exotic understory plants in deciduous forests. Ecological Applications 11:1287–1300. Gurevitch, J., G.A. Fox, G.M. Wardle, Inderjit, and D. Taub. 2013. Emergent insights from the synthesis of conceptual frameworks for biological invasions. Ecology Letters 14:407–418. Haissig, B.E., and R.E. Dickson. 1979. Starch measurement in plant tissue using enymatic hydrolysis. Physiologia Plantarum 47:151–157. Herberling, J.M., and J.D. Fridley. 2013. Resource-use strategies of native and invasive plants in Eastern North American forests. New Phytologist 200:523–533. Karl, T.R., J.M. Melillo, and T.C. Peterson (Eds.). Global Climate Change Impacts in the United States. 2009. Cambridge University Press, New York, NY. 196 pp. Keane, R.M., and M.K. Crawley. 2002. Exotic plant invasions and the enemy-release hypothesis. TRENDS in Ecology and Evolution 17:164–169. Kourtev, P.S., W.Z. Huang, and J.G. Ehrenfeld. 1999. Differences in earthworm densities and nitrogen dynamics in soils under exotic and native plant species. Biological Invasions 1:237–245. Leishman, M.R., T. Haslehurst, A. Ares, and Z. Baruch. 2007. Leaf-trait relationships of native and invasive plants: Community- and global-scale comparisons. New Phytologist 176:635–643. Moles, A.T., H. Flores-Moreno, S.P. Bonser, D.I. Warton, A. Helm, L. Warman, D.J. Eldridge, E. Jurado, F.A. Hemmings, P.B. Reich, J. Cavender-Bares, E.W. Seabloom, M.M. Mayfield, D. Sheil, J.C. Djietror, P.L. Peri, L. Enrico, M.R. Cabido, S.A. Setterfield, C.E.R. Lehmann, and F.J. Thomson. 2012. Invasions: The trail behind, the path ahead, and a test of a disturbing idea. Journal of Ecology 100: 116–127. Northeastern Naturalist Vol. 22, No. 2 D. Vanderklein, A. Cullen, and J.-E. Belcourt 2015 261 Pimentel, D., L. Lach, R. Zuniga, and D. Morrison. 2000. Environmental and economic costs of nonindigenous species in the United States. BioScience 50:53–65. Pratt, P.D., M.B. Rayamajhi, T.K. Van, T.D. Center, and P.W. Tipping. 2005. Herbivory alters resource allocation and compensation in the invasive tree Melaleuca quinquenervia. Ecological Entomology 30 316–326. Reich, P.B., M.B. Walters, S.D. Krause, D. Vanderklein, K.F. Raffa, and T.T. Tabone. 1993. Growth, nutrition, and gas exchange of Pinus resinosa following artificial defoliation. Trees 7:67–77. Reich, P.B., M.B. Walters, and D.S. Ellsworth. 1997. From tropics to tundra: Global convergence in plant functioning. Proceedings of the National Academy of Sciences 94:13,730–13,734. Reich, P.B., D.S. Ellsworth, M.B. Walters, J.M. Vose, C.G. Gresham, J.C. Volin, and W.D. Bowman. 1999. Generality of leaf-trait relationships: A test across six biomes. Ecology 80:1955–1969. Schierenbeck, K.A., R.N. Mack, and R.R. Sharitz. 1994. Effects of herbivory on growth and biomass allocation in native and introduced species of Lonicera. Ecology 75:1661–1672. Schlaepfer, D.R., M. Glättli, M. Fischer, and M. van Kleunen. 2009. A multi-species experiment in their native range indicates pre-adaptation of invasive alien plant species. New Phytologist 185:1087–1099. Silander, J.A., and D.M. Klepeis. 1999. The invasion of Japanese Barberry (Berberis thunbergii) in the New England landscape. Biological Invasions 1:189–201. Snyder, D., and S.R. Kaufman. 2004. An overview of nonindigenous plant species in New Jersey. New Jersey Department of Environmental Protection, Division of Parks and Forestry, Office of Natural Lands Management, Natural Heritage Program, Trenton, NJ. 107 pp. Stastny, M., U. Schaffner, and E. Elle. 2005. Do vigor of introduced populations and escape from specialist herbivores contribute to invasiveness? Journal of Ecology 93:27–37. Trumble, J.T., D.M. Kolodny-Hirsch, and I.P. Ting. 1993. Plant compensation for arthropod herbivory. Annual Review of Entomology 38:93–119. Vanderklein, D.W., and P.B. Reich. 1999. The effect of defoliation intensity and history on photosynthesis, growth, and carbon reserves of two conifers with contrasting leaf lifespans and growth habits. New Phytologist 144:121–132. Vanderklein, D.W., E. Daquila, and E. Corrozza. 2000. White Pine, Japanese Larch, and Bear Oak respond differently to partial defoliation. Northeastern Naturalist 8:319– 330. Xu, C.-Y., K.L. Griffin, and W.S.F. Schuster. 20009. Leaf phenology and seasonal variation of photosynthesis of invasive Berberis thunbergii (Japanese Barberry) and two co-occuring native understory shrubs in a northeastern United States deciduous forest. Ecology 154:11–21.