Differences in Leaf Functional Traits Between Rhus Typhina and Native Species 1School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, P

CSAWAC 44 (11) 1429-1598 (2016) · Vol. 44 · No. 11 · November 2016 CLEAN Soil Air Water

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Congyan Wang1,2 Research Article Jun Liu1 Hongguang Xiao1 Jiawei Zhou1 Differences in Leaf Functional Traits Between Rhus typhina and Native Species 1School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, P. R. China The differences in leaf functional traits between invasive and native species are 2State Key Laboratory of Soil and considered to be closely linked to the mechanisms underlying successful plant invasion Sustainable Agriculture, Institute of because co-occurring invasive and native species experience similar or even identical Soil Science, Chinese Academy of environmental selective pressures. This study aims to determine the differences in leaf Sciences, Nanjing, P. R. China functional traits and resource-use strategy between the invader Rhus typhina and the native species Sapindus mukorossi. Leaf chlorophyll and nitrogen concentrations, specific leaf area (SLA), and leaf moisture of R. typhina were significantly higher than those of S. mukorossi, but leaf length, leaf width, and single-leaf wet and dry weights of R. typhina were significantly lower than those of S. mukorossi. Plasticity indices of leaf shape index and SLA of R. typhina were obviously higher than those of S. mukorossi, while plasticity indices of single-leaf wet and dry weights, and leaf moisture of R. typhina were obviously lower than those of S. mukorossi. The higher leaf chlorophyll and nitrogen concentrations, SLA, and leaf moisture as well as the high range of phenotypic plasticity of leaf shape index and SLA for R. typhina may confer it a competitive advantage and thus play an important role in its successful invasion.

Keywords: Environmental changes; Invasive species; Leaf functional traits; Phenotypic plasticity; Specific leaf area Received: February 22, 2016; revised: May 31, 2016; accepted: June 20, 2016 DOI: 10.1002/clen.201600144

1 Introduction Invasive plants have triggered serious threats to native ecosystems, changing the structure and function of the ecosystems in Leaves play an important role in plant development, growth, and which those invasions occur [11–13]. Numerous studies have survival [1, 2]. Leaves influence the acquisition of sunlight, which is revealed that certain plants successfully invade certain environ- perhaps one of the most important environmental factors that ments because leaf functional traits (such as higher SLA) of those influence plant growth [1, 2]. Thus, the response of leaf functional invaders can enable them to acquire more resources and grow at a traits to changes in environmental factors can improve the high growth rate than co-occurring native species [14–17]. The adaptability of plants in a wide variety of habitats and then expand differences in leaf functional traits between invasive and native their ecological niche because leaves are exposed to a multivariate species are believed to be closely linked to the mechanisms environment and are sensitive to environmental changes [3–7]. As underlying the success of plant invasions because co-occurring one of the most crucial leaf functional traits, specific leaf area (SLA) invasive and native species in the same ecosystem experience similar can indicate the resource-use strategy of plants [3, 8, 9]. SLA is or even identical environmental selective pressures [14, 18]. defined as the investment of sunlight capture surface per unit area This study aims to determine the differences in leaf functional of leaf [3, 8, 9]. Normally, high SLA indicates high resource traits of the controversial invader Rhus typhina and the native species acquisition and use efficiency with low investment in leaf Sapindus mukorossi. The two species can coexist in the same construction and protective tissues [3, 8, 9]. Leaf size, leaf thickness, ecosystem. Both are members of the Sapindales order. R. typhina is leaf shape index, single-leaf wet and dry weights, and leaf moisture a deciduous tree native to Canada and the United States and was are also important indices of leaf functional traits as they can introduced to China in 1959 as a common forestry species by the indicate the resource-use strategy of plants [3, 5–7, 10]. Hence, Botanical Garden of the Institute of Botany in the Chinese Academy determining the leaf functional traits of plants is an important part of Sciences [19, 20]. This species also has some ornamental value of enucleating the mechanism underlying their successful ecologi- because of its fruit clusters, which look like burning torches in late cal strategy. summer and early autumn, and because of its brilliant red foliage in mid-autumn [19]. Meanwhile, the species can demonstrate vigorous growth even in poor soils [19, 21]. For this reason, it is frequently used for rehabilitation of degraded lands in most mountain areas of Correspondence: Dr. Congyan Wang, School of the Environment and north China [19, 21]. However, the species possesses somewhat Safety Engineering, Jiangsu University, No. 301, Xuefu Road, Zhenjiang invasive characteristics such as vigorous growth and rapid 212013, P. R. ChinaE-mail: [email protected] reproduction [19, 21]. To date, the species has spread into almost Abbreviations: SLA, specific leaf are. all habitats from urban to montane, including roadsides, farmlands,

© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.clean-journal.com Clean – Soil, Air, Water 2016, 44 (11), 1591–1597 1592 C. Wang et al. and protected areas [19]. Thus, R. typhina has been identified as a SLAwas computed using the ratio of theleaf areato thecorresponding destructive invader by many botanists [19, 22]. leaf dry weight (cm2 g1), following previous studies [5–8, 28]. In this study, leaf functional traits (i.e., leaf size [indicated by Leaf moisture was calculated by subtracting the leaf dry weight leaf length and leaf width], leaf shape index, leaf chlorophyll and from the leaf wet weight; the difference was then divided by the leaf nitrogen concentrations, SLA, single-leaf wet and dry weights, wet weight [5, 6]. Single-leaf wet weight was determined using an leaf moisture, and leaf thickness) of R. typhina and S. mukorossi electronic balance. Single-leaf dry weight was obtained by initially were assessed to gain insight into their ecological strategies. subjecting the samples to oven-drying at 60°C for 24 h to achieve The results of this study can provide a platform for better a constant weight; the final single-leaf dry weight was then understanding the mechanisms underlying the successful inva- determined using an electronic balance with an accuracy of sion of R. typhina, and may establish an important theoretical 0.001 g [5, 6]. foundation and carry practical significance for effective invasion Leaf thickness was calculated by overlaying five leaves and prevention and control. This study presents the following measuring their combined thickness using a Vernier caliper with an hypotheses. First, the SLA of R. typhina maybehigherthanthat accuracy of 0.01 mm [5–7]. of S. mukorossi because invasive species invest more biomass in Plasticity indices (the index ranged from zero (no plasticity) to one leaf growth rather than leaf structures per unit area to achieve a [maximum plasticity]) of plant characteristics were calculated with higher growth rate than native species [14–17]. In particular, a the following equation [29]: higher SLA is often correlated with a growth advantage for invasive species over native species [23, 24]. Second, the plasticity Maximum minimum Plasticity index ¼ mean mean ð1Þ index of R. typhina may be higher than that of S. mukorossi because Maximummean higher phenotypic plasticity can allow plants to enhance their adaptability via the higher phenotypic plasticity in response to the changes in environmental factors [14, 15]. More importantly, 2.3 Statistical analysis the phenotypic plasticity of invasive species is known to be positively correlated with their invasiveness [14, 25]. Third, leaf One-way ANOVA was performed to evaluate the differences in leaf thickness, and single-leaf wet and dry weights are likely to be functional traits of the two species. Correlation analysis was negatively correlated with SLA; by contrast, leaf size, leaf performed using Pearson product-moment correlation coefficient to chlorophyll and nitrogen concentrations, and leaf moisture are determine the patterns among various dependent variables. All likely to be positively correlated with SLA because leaves with low statistical analyses were performed using SPSS Statistics (version SLAslikelyinvestgreatbiomassinleafstructures,butleaveswith 22.0; IBM, Armonk, NY). Then, a Mantel test [30] was conducted using high SLAs require low structural investment [3, 9, 10]. TFPGA (version 1.3) to quantify the relationships given in the correlation matrix between leaf functional traits of R. typhina and those of S. mukorossi. Statistical significance was set at p-values equal 2 Materials and methods to or <0.05. 2.1 Experimental design

In mid-August 2015, plant samples were collected in Jinan, P. R. 3 Results China (36.63°N, 117.03°E) which has a warm temperate climate. Leaf chlorophyll and nitrogen concentrations, SLA, and leaf The annual mean temperature of the area is approximately moisture of R. typhina were significantly higher than those of 13.8°C, and the monthly mean temperature reaches a maximum S. mukorossi (Tabs. 1 and 2, p < 0.01). By contrast, leaf length, leaf of 27.2°C in July and decreases to a minimum of 3.2°C in width, and single-leaf wet and dry weights of R. typhina were January. Annual precipitation is approximately 614 mm and the significantly lower than those of S. mukorossi (Tabs. 1 and 2, monthly mean precipitation reaches a maximum of 196 mm in p < 0.0001). No significant difference was observed in leaf shape July and decreases to a minimum of 7 mm in January. Fifteen index and leaf thickness between R. typhina and S. mukorossi (Tabs. 1 plant individuals for each species were collected randomly. Five and 2, p > 0.05). mature, intact leaves of one plant sample were selected randomly Plasticity indices of the leaf shape index and SLA of R. typhina were to determine the leaf functional traits. All samples were stored in obviously higher than those of S. mukorossi (Tab. 3). Plasticity indices sealed bags and immediately transported to the laboratory for of single-leaf wet and dry weights as well as leaf moisture of analysis. R. typhina were obviously lower than those of S. mukorossi (Tab. 3). There was no significant difference in plasticity indices of other indices of leaf functional traits between R. typhina and S. mukorossi 2.2 Determination of plant characteristics (Tab. 3). The leaf shape index was calculated as the ratio of leaf length to the Correlation patterns among leaf functional traits for each species corresponding leaf width [5, 6, 26, 27]. The leaf length is the were observed through correlation analysis (Tab. 4). Leaf length was maximum value along the midrib, while the width is the maximum positively correlated with SLA for R. typhina (Tab. 4, p < 0.01) and with value perpendicular to the midrib [27]. Leaf length and leaf width leaf width as well as single-leaf wet and dry weights for S. mukorossi were measured using a ruler [5–7]. (Tab. 4, p < 0.01). Leaf width was negatively correlated with the leaf The relative chlorophyll and N concentrations in the leaves were shape index for both R. typhina and S. mukorossi (Tab. 4, p < 0.05). estimated with a hand-held plant nutrient meter (TYS-3N, P. R. Meanwhile, leaf width was also positively correlated with single- China). TYS-3N was used to calculate the index in “SPAD units” based leaf wet and dry weights for S. mukorossi (Tab. 4, p < 0.01). The on absorbance at 650 and 940 nm [7]. leaf chlorophyll concentration was positively correlated with the

© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.clean-journal.com Clean – Soil, Air, Water 2016, 44 (11), 1591–1597 General 1593 ns ns leaf nitrogen concentration for both R. typhina and S. mukorossi

0.01 0.01 (Tab. 4, p < 0.0001). SLA was positively correlated with leaf moisture (Tab. 3, p < 0.01) but negatively correlated with single-leaf dry weight c leaf area; ﬁ 0.33 0.33 for R. typhina (Tab. 4, p < 0.05). Single-leaf wet weight was positively correlated with leaf thickness for R. typhina (Tab. 4, p < 0.05) and with

a b single-leaf dry weight for S. mukorossi (Tab. 4, p < 0.0001). Single-leaf

1.20 3.23 dry weight was negatively correlated with leaf moisture for both

R. typhina and S. mukorossi (Tab. 4, p < 0.05). Mantel tests (r ¼ 0.31, p ¼ 0.0240) showed a positively signiﬁcant relationship between the 62.58 52.23 correlation patterns among leaf functional traits of R. typhina and those of S. mukorossi as indicated by the correlation matrix. b a 0.00 0.03 s; LW, leaf width; SLA, speci

4 Discussion

0.11 0.29 Numerous studies suggest that invasive plants should invest more biomass in leaf growth rather than leaf structures per unit leaf area

b a to obtain a higher growth rate [14–16, 24]. Meanwhile, higher SLA is

0.01 0.05 often correlated with a growth advantage for invasive plants over

native species [23, 24]. It was therefore expected that the SLA of the focal invasive plants would be higher than that of the focal native 0.29 0.60 species. The results of this study showed that the SLA of R. typhina ﬁ a was signi cantly higher than S. mukorossi. This was consistent with ) SLWW (g) SLDW (g) LM (%) LT (mm) b 1

the study’s ﬁrst hypothesis. In addition, leaf chlorophyll and g 2 13.72 5.52 nitrogen concentrations, and leaf moisture of R. typhina were also signiﬁcantly higher than those of S. mukorossi. This indicated that R. typhina possess higher resource capture ability as well as higher 222.18 170.84 relative growth rate than co-occurring S. mukorossi, suggesting that those traits may play a little-understood role during the process of ) SLA (cm 1 a b 0.05).

successful invasion of R. typhina. However, there is a debate on the > 0.11 0.05

p difference in SLA between invasive and native species: i.e., invasive

plants may display higher [14–17, 24, 31], similar [32–34], or even lower [35–37] SLA values compared with native species. Numerous 4.46 3.24 studies found that leaves development is very closely associated with 0.05).

< the spatial and temporal heterogeneity of the environment (such as a b p soil temperature, air temperature, and sunlight environment), in cant difference ( 1.60 0.85

ﬁ which plants have evolved [38–40]. Thus, the difference in SLA between invasive and native species may also be due to their

55.34 37.72 different growth environmental conditions. Previous studies have

S. mukorossi also revealed mixed results when quantifying the relationship cant difference (

and between relative growth rate and SLA. The relationship may be ﬁ ns ns positive [3, 41], negative [42, 43], absent [35], or variable amongst 0.12 0.08 habitats [44] and growth periods [45]. Thus, the relationship between relative growth rate and SLA appears to be species-speciﬁc. R. typhina 3.63 3.52 Meanwhile, R. typhina showed similar leaf shape index and leaf thickness and lower leaf length, leaf width, and single-leaf wet and b a dry weights compared with S. mukorossi. Thus, the invasiveness of

0.11 0.15 R. typhina cannot be explained by those indexes. Some studies showed that phenotypic plasticity should be a

2.96 4.26 potential target for selection because the functional traits that could confer a ﬁtness advantage to plants in their habitats will be under

b a selective pressure and may thus evolve [3, 46]. Thus, the phenotypic ’ 0.27 0.43 plasticity of any functional traits related to plants performance and ﬁtness may play a little-understood role in their successful survival [3, 14, 46]. This study found that all examined leaf functional traits of 10.61 LL (cm) LW (cm) LSI LCC (SPAD) LNC (mg g 14.89 the two species display phenotypic plasticity. Those leaf functional traits displaying a certain extent of phenotypic plasticity may be

Differences in leaf functional traits between inﬂuenced by the local adaptation of plants in the multivariate environment. The phenotypic plasticity of leaf functional traits in response to environment changes may allow plants to possess a R. typhina SLDW, single-leaf dry weight;Data SLWW, with single-leaf different wet letters weight; in ns, a no vertical signi row indicate a signi Table 1. S. mukorossi LCC, leaf chlorophyll concentration; LL, leaf length; LM, leaf moisture; LNC, leaf nitrogen concentration; LSI, leaf shape index; LT, leaf thicknes competitive advantage and especially to broaden their habitat niche.

Table 2. ANOVA of the effects of species on leaf functional traits

Sum of squares df Mean square Fp

LL Between groups 137.25 1 137.25 71.89 <0.0001 Within groups 53.46 28 1.91 Total 190.70 29 LW Between groups 12.59 1 12.59 49.67 <0.0001 Within groups 7.10 28 0.25 Total 19.68 29 LSI Between groups 0.09 1 0.09 0.59 0.4489 Within groups 4.40 28 0.16 Total 4.49 29 LCC Between groups 2330.25 1 2330.25 95.01 <0.0001 Within groups 686.76 28 24.53 Total 3017.01 29 LNC Between groups 11.00 1 11.00 92.51 <0.0001 Within groups 3.33 28 0.12 Total 14.33 29 SLA Between groups 19 769.58 1 19 769.58 12.06 0.0017 Within groups 45 916.86 28 1639.89 Total 65 686.44 29 SLWW Between groups 0.71 1 0.71 44.26 <0.0001 Within groups 0.45 28 0.02 Total 1.15 29 SLDW Between groups 0.24 1 0.24 32.87 <0.0001 Within groups 0.21 28 0.01 Total 0.45 29 LM Between groups 802.26 1 802.26 8.99 0.0056 Within groups 2498.05 28 89.22 Total 3300.31 29 LT Between groups 0.00 1 0.00 0.01 0.9394 Within groups 0.05 28 0.00 Total 0.05 29

LCC, leaf chlorophyll concentration; LL, leaf length; LM, leaf moisture; LNC, leaf nitrogen concentration; LSI, leaf shape index; LT, leaf thickness; LW, leaf width; SLA, speciﬁc leaf area; SLDW, single-leaf dry weight; SLWW, single-leaf wet weight. p-values equal to or <0.05 are in bold print.

It was therefore expected that the phenotypic plasticity of leaf species showed similar [31, 47] or even lower [31, 48, 49] phenotypic functional traits of invasive species may be higher than the plasticity compared with native species because the lower plasticity phenotypic plasticity of native species. This study showed that of leaf functional traits could compensate for the negative effects of phenotypic plasticity of leaf shape index and SLA was higher for adverse environments and facilitate invasion [31, 46]. Hence, R. typhina than S. mukorossi. Phenotypic plasticity of leaf shape index phenotypic plasticity of leaf functional traits of invasive species and SLA for invasive species may enable them to gain advantage in may play an important role in the successful invasion of some increasing resource (especially sunlight) capture and use efficiency. invasive species, but not all. However, this study also found that phenotypic plasticity of single- Numerous studies suggest that leaf size is positively correlated leaf wet and dry weights and leaf moisture of R. typhina was with SLA because leaves with high SLA require low structural unexpectedly lower for R. typhina than for S. mukorossi,afinding that investment, but leaves with low SLA likely invest more biomass on was less consistent with the study’s second hypothesis. This may leaf structures [3, 9, 10]. SLA was related to leaf length for only indicate that phenotypic plasticity of some but not all leaf R. typhina in this study. This result is consistent with those of functional traits of invasive species play an important role in their previous studies [3, 9, 10]. However, there was no significant successful invasion. Moreover, previous studies examining the correlation between leaf size and SLA for S. mukorossi. Meanwhile, relationship between phenotypic plasticity and plant invasion leaves with higher SLAs normally allocate less biomass to leaf obtained similarly mixed results. Some studies have found that construction with the aim of obtaining high resource acquisition invasive plants exhibit higher plasticity than native species, and and use efficiency and thus display lower leaf thickness and single- higher phenotypic plasticity was considered the main driver of leaf wet and dry weights but higher leaf chlorophyll and nitrogen successful invasion [14, 15]. Other studies revealed that invasive concentrations and leaf moisture [3, 9, 46]. The result of this study

Table 3. Differences in plasticity indices of leaf functional traits between R. typhina and S. mukorossi

LL (cm) LW (cm) LSI LCC (SPAD) LNC (mg g1) SLA (cm2 g1) SLWW (g) SLDW (g) LM (%) LT (mm)

R. typhina 0.29 0.43 0.43 0.27 0.24 0.58 0.29 0.34 0.25 0.35 S. mukorossi 0.34 0.39 0.29 0.23 0.18 0.36 0.63 0.64 0.38 0.39

revealed that SLA was positively correlated with leaf moisture but traits of R. typhina and those of S. mukorossi are similar. Thus, the negatively correlated with single-leaf dry weight for R. typhina only. main factor influencing the successful invasion of R. typhina may be Unfortunately, SLA did not have a significant relationship with leaf the difference in individual leaf functional traits between R. typhina chlorophyll and nitrogen concentrations, single-leaf wet weight, or and the native species rather than the difference in the correlation leaf thickness in this study. Consequently, the results were only patterns among leaf functional traits between R. typhina and the partly consistent with the study’s third hypothesis. According to the native species. Mantel test, there was a significant positive correlation pattern In brief, the higher leaf chlorophyll and nitrogen concentrations, between leaf functional traits of R. typhina and those of S. mukorossi. SLA, and leaf moisture as well as the high range of phenotypic This implied that the correlation patterns between leaf functional plasticity of leaf shape index and SLA of R. typhina may permit a

Table 4. Relationship among leaf functional traits of R. typhina (RT) and S. mukorossi (SM)

LL (cm) LW (cm) LSI LCC (SPAD) LNC (mg g1) SLA (cm2 g1) SLWW (g) SLDW (g) LM (%) LT (mm)

LL (cm) RT r 1.00 0.27 0.39 0.04 0.02 0.65 0.42 -0.13 0.44 0.33 p 0.3254 0.1457 0.8840 0.9478 0.0094 0.1173 0.6551 0.1023 0.2305 SM r 1.00 0.79 0.07 0.40 0.43 0.13 0.74 0.74 0.33 0.17 p 0.0005 0.8097 0.1395 0.1108 0.6328 0.0017 0.0015 0.2262 0.5376 LW (cm) RT r 1.00 0.76 0.29 0.36 0.27 0.40 0.02 0.30 0.17 p 0.0009 0.2932 0.1857 0.3349 0.1393 0.9506 0.2854 0.5513 SM r 1.00 0.55 0.25 0.34 0.01 0.78 0.71 0.19 0.24 p 0.0321 0.3596 0.2162 0.9777 0.0007 0.0031 0.5031 0.3799 LSI RT r 1.00 0.27 0.34 0.18 0.08 0.06 0.01 0.14 p 0.3284 0.2130 0.5269 0.7766 0.8185 0.9742 0.6180 SM r 1.00 0.09 0.00 0.25 0.24 0.10 0.17 0.11 p 0.7554 0.9971 0.3767 0.3919 0.7172 0.5338 0.6871 LCC (SPAD) RT r 1.00 1.00 0.03 0.29 0.34 0.10 0.17 p <0.0001 0.9181 0.2955 0.2117 0.7324 0.5505 SM r 1.00 0.91 0.23 0.29 0.21 0.02 0.28 p <0.0001 0.4049 0.2971 0.4502 0.9372 0.3095 LNC (mg g–1)RTr 1.00 0.02 0.32 0.35 0.08 0.13 p 0.9309 0.2476 0.1945 0.7657 0.6376 SM r 1.00 0.18 0.38 0.23 0.12 0.10 p 0.5273 0.1599 0.4179 0.6651 0.7111 SLA (cm2 g–1)RTr 1.00 0.24 0.57 0.76 0.21 p 0.3954 0.0255 0.0010 0.4425 SM r 1.00 0.27 0.42 0.32 0.06 p 0.3220 0.1167 0.2500 0.8453 SLWW (g) RT r 1.00 0.44 0.38 0.55 p 0.1039 0.1596 0.0334 SM r 1.00 0.85 0.12 0.46 p <0.0001 0.6731 0.0822 SLDW (g) RT r 1.00 0.66 0.47 p 0.0073 0.0744 SM r 1.00 0.62 0.38 p 0.0146 0.1668 LM (%) RT r 1.00 0.05 p 0.8479 SM r 1.0000 0.0389 p 0.8906 LT (mm) RT r 1.00 p SM r 1.00 p

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