Gas exchange and growth responses to nutrient enrichment in invasive Glyceria maxima and native New Zealand Carex species

Aquatic Botany 103 (2012) 37–47

Contents lists available at SciVerse ScienceDirect

Aquatic Botany journal homepage: www.elsevier.com/locate/aquabot

Gas exchange and growth responses to nutrient enrichment in invasive Glyceria maxima and native New Zealand Carex species Brian K. Sorrell a,∗ , Hans Brix b , Isla Fitridge a,1 , Dennis Konnerup b , Carla Lambertini b a b

National Institute of Water and Atmospheric Research, Christchurch 8440, New Zealand Department of Bioscience, Plant Biology, Aarhus University, DK-8000 Aarhus C, Denmark

a r t i c l e

i n f o

Article history: Received 18 September 2011 Received in revised form 25 May 2012 Accepted 30 May 2012 Available online 15 June 2012 Keywords: Carbon assimilation Light response Nitrogen Photosynthesis Wetland

a b s t r a c t We compared photosynthetic gas exchange, the photosynthesis–leaf nitrogen (N) relationship, and growth response to nutrient enrichment in the invasive wetland grass Glyceria maxima (Hartman) Holmburg with two native New Zealand Carex sedges (C. virgata Boott and C. secta Boott), to explore the ecophysiological traits contributing to invasive behaviour. The photosynthesis–nitrogen relationship was uniform across all three species, and the maximum light-saturated rate of photosynthesis expressed on a leaf area basis (Amax a ) did not differ significantly between species. However, specific leaf area (SLA) in G. maxima (17 ± 6 m2 kg−1 ) was 1.3 times that of the sedges, leading to 1.4 times higher maximum rates of photosynthesis (350–400 nmol CO2 g−1 dry mass s−1 ) expressed on a leaf mass basis (Amax m ) when N supply was unlimited, compared to the sedges (<300 nmol CO2 g−1 dry mass s−1 ). Analysis of Covariance (ANCOVA) revealed significant positive relationships between leaf N content and chlorophyll a:b ratios, stomatal conductance (gs ), dark respiration rate (Rd ), and the photosynthetic light saturation point (Ik ) in G. maxima, but not in the sedges. ANCOVA also identified that, compared to G. maxima, the sedges had 2.4 times higher intrinsic water use efficiency (A/gs : range 20–70 cf. 8–30 ␮mol CO2 mol−1 H2 O) and 1.6 times higher nitrogen use efficiency (NUE: 25–30 cf. 20–23 g dry mass g−1 N) under excess N supply. Relative growth rates (RGR) were not significantly higher in G. maxima than the sedges, but correlations between leaf N, gas exchange parameters (Amax a , Amax m , Rd and gs ) and RGR were all highly significant in G. maxima, whereas they were weak or absent in the sedges. Allocation of biomass (root:shoot ratio, leaf mass ratio, root mass ratio), plant N and P content, and allocation of N to leaves all showed significantly greater phenotypic plasticity and stronger correlation to final biomass in G. maxima than in the sedges. We therefore conclude that photosynthesis and growth rates are not intrinsically higher in this invader than in the native species with which it competes, but that its success under nutrient enrichment is a consequence of greater physiological responsiveness and growth plasticity, and stronger integration between gas exchange and growth, coupled with indifference to resource wastage (i.e. low WUE and NUE) at high nutrient supply. The poorer performance of G. maxima than the sedges under low nutrient supply supports the importance of nutrient management, especially N, as a strategy to minimise the invasive behaviour of fast-growing herbaceous species in wetlands. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Biological invasions are one of the most important problems affecting the biodiversity, species composition, structure and function of ecosystems (Parker et al., 1999; Simberloff, 2004). Wetland ecosystems are particularly prone to weed invasion, espe-

∗ Corresponding author at: Department of Bioscience, Plant Biology, Aarhus University, Ole Worms Allé 1, DK-8000 Aarhus C, Denmark. Tel.: +45 23 66 68 64; fax: +45 89 42 47 47. E-mail address: [email protected] (B.K. Sorrell). 1 Current address: Department of Zoology, University of Melbourne, Parkville, Victoria 3010, Australia. 0304-3770/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.aquabot.2012.05.008

cially when subjected to hydrological changes, nutrient inputs and physical disturbance (Ehrenfeld, 2008). This is due to their landscape sink position, in which water, sediment and nutrients accumulate, favouring vigorous, competitive species (Zedler and Kercher, 2004). No single factor can explain all successful invasions, or apply to every invasive plant species. Nevertheless, the prevalence of anthropogenic flooding and nutrient enrichment in wetlands has often favoured invaders that can rapidly acquire nutrients under high supply, and thereby compete for light and increase growth more than native species (Keddy, 2010). Species from almost all plant growth forms have become invasive in wetlands, and their invasiveness often involves traits associated with superior exploitation of nutrients and light, including rapid growth, clonal growth, high rates of litter production, and high

38

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

investment in above-ground biomass (Keddy, 2005). Making invasion biology a predictive science remains a major challenge, however, as relatively few traits are unambiguously associated with invasiveness (Pyˇsek and Richardson, 2007). Instead, high phenotypic plasticity (i.e. change in phenotypic expression in response to environmental factors – Davidson et al., 2011) of key traits associated with growth is often a feature of invasive plants (Funk, 2008; Davidson et al., 2011). The significance of phenotypic plasticity for plant invasions in aquatic and wetland environments has received little attention, but appears to be important for wetland invaders such as Lythrum salicaria L. (Mal and Lovett-Doust, 2005). Whenever nutrient enrichment facilitates invasion, differences in photosynthetic gas exchange are likely to be an important consideration. Light-saturated photosynthesis rates are strongly related to the nitrogen (N) content of leaves due to N investment in Rubisco, chlorophyll (Chl), other photosynthetic enzymes and pigments, and thylakoid membrane proteins (Sugiharto et al., 1990; Reich et al., 1998; Evans and Poorter, 2001). Higher nutrient concentrations in tissues associated with growth, especially leaves, and associated higher rates of photosynthesis have been identified in several successful terrestrial invaders compared with native competitors (Durand and Goldstein, 2001; Feng et al., 2009); this is also true for wetland invaders such as Phragmites australis (Cav.) Trin ex Steud. (Farnsworth and Meyerson, 2003), Typha domingensis Presl. (Li et al., 2009), and Spartina alterniflora Loisel. (Jiang et al., 2009). However, many of the features underlying photosynthesis–nitrogen and growth relationships, such as differences between area-based and mass-based rates of photosynthesis (Poorter et al., 1990; Reich et al., 1998) and potential trade-offs (Lambers et al., 2008) between nitrogen use efficiency (NUE) and water use efficiency (WUE), have received little attention in the wetland environment. As the high apparent primary productivity in wetlands is often attributed to excess water and nutrient availability (Childers, 2006; Keddy, 2010), interspecific differences in morphological, photosynthetic and growth responses to nutrients may be particularly important in explaining the success of invaders in these environments. One important invasive species in wetlands is reed sweetgrass (G. maxima (Hartman) Holmburg), a temperate aquatic grass indigenous to Eurasia, behaving invasively in North America (Anderson and Reznicek, 1994; Wei and Chow-Fraser, 2006), Australasia (Champion et al., 2002; Clarke et al., 2004), and even its home range (Nurminen, 2003). Invasion of G. maxima is clearly linked to nutrient levels, with elevated concentrations of both nitrogen and phosphorus in soils correlating strongly with its establishment and success (Loo et al., 2009). Given that its growth and investment in shoot biomass is highly responsive to elevated N (Munzarová et al., 2005), it may be a particularly useful species for exploring how enhanced photosynthetic capacity contributes to the success of an invader in nutrient-enriched wetlands. The aim of this study was therefore to contrast the nutrient responses of gas exchange and growth in this species against native wetland competitors, viz. two Carex species (C. virgata Boott and C. secta Boott) common in minerotrophic swamps and marshes in New Zealand. Both are tall, productive species that are canopy dominants (Johnson and Gerbeaux, 2004), in wetlands where G. maxima thrives and frequently is invasive. Specifically, we addressed three hypotheses concerning possible differences in photosynthetic and growth physiology that may be involved in superior performance of an invasive species under nutrient enrichment: that the invader has (i) higher photosynthetic activity and growth rates than the natives under high nutrient availability; (ii) higher investment in above-ground biomass and greater allocation of N to leaves under high nutrient availability; and (iii) greater phenotypic plasticity in growth, morphological and physiological traits associated with

competition under high fertility, allowing a greater response to increased nutrient supply. 2. Materials and methods 2.1. Plant materials and experimental design We carried out our experiment at the Silverstream Research Facility, 15 km north of Christchurch, New Zealand (43◦ 33 S, 172◦ 47 E). The experiment ran outdoors under ambient light and climatic conditions during the late austral summer months of February–April (mean daily solar radiation = 15 MJ m−2 , mean daily air temperature = 15.0 ◦ C, mean relative humidity = 65.5%) with plants grown in individual polythene planter bags (0.5 m height, 0.3 m diameter). The bags were randomised in concrete runways in which they were permanently flooded to the substrate surface throughout the experiment with a continuous through-flow of water from the adjacent spring-fed Kaiapoi River, which has a constant temperature of 12 ◦ C. All bags were placed in situ six weeks prior to planting, to allow them to equilibrate under flooded conditions and develop wetland hydrology, as evidenced by redox potentials < 200 mV indicative of soil anoxia, measured with platinum wire electrodes according to Faulkner et al. (1989). To create three fertility levels ranging from severely nutrient-limited to excess, and hence a gradient in nutrient availability suitable for testing the hypotheses of this experiment, substrates in the bags consisted of (i) washed river sand; (ii) a locally sourced loam soil; and (iii) a fertilised treatment consisting of the loam soil with added slow-release fertiliser (Yates Magamp, Yates NZ Ltd.) plus a weekly addition of liquid fertiliser (Yates Thrive, Yates NZ Ltd.). Nutrient availability therefore comprised nutrients available in the substrates and the through-flowing river water. N and P concentrations in substrates of unplanted control bags sampled at the end of the experiment ranged from <90 mgN kg−1 dry mass and <300 mgP kg−1 dry mass in the sand substrate, to 700 mgN kg−1 dry mass and 450 mgP kg−1 dry mass in the soil, and >2000 mgN kg−1 dry mass and >800 mgP kg−1 dry mass in the fertilised substrate. We obtained four week old seedlings of the Carex species, grown from locally collected seed, from a specialist native plant nursery (Motukarara Conservation Nursery, Christchurch, New Zealand), and collected wild ramets of G. maxima from a population at a nearby river mudflat, taking care to select similar-sized individuals to the Carex seedlings. Five seedlings of each species were separated into shoots and roots and fresh and dry masses measured for initial biomass. The remaining seedlings were then transferred into the pre-equilibrated bags for experiments (n = 5 per treatment per species, i.e. total of 45 randomised planted bags). Leaf gas exchange measurements and harvests were carried out after 56 days (Carex spp.) and 43 days (G. maxima), when plants were of a similar maximum size in pots and hence growth responses and biomass partitioning were not confounded by ontogenetic change (McConnaughay and Coleman, 1999). 2.2. Leaf gas exchange We made leaf gas exchange measurements using an open system infrared gas analyzer (ADC LCi, Analytical Development Co. Bioscientifics Ltd., Hoddesdon, UK). Each plant was treated as an individual replicate, and each measurement was conducted on the third-youngest (G. maxima) or third and fourth youngest (Carex spp.) fully expanded leaves. Conditions in the chamber were 363–367 ppm CO2 concentration in the incoming air, 20.6 ± 1.3 ◦ C air temperature and 55% relative air humidity. Gas exchange results were calculated per unit leaf area, by multiplying the sum of leaf widths with chamber length (2.5 cm) for one-sided leaf area. The

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

39

chamber was illuminated with a white halogen source (Portable Light Unit, ADC Bioscientifics Ltd., UK), initially at a photosynthetic photon flux density (PPFD) of 913 ␮mol m−2 s−1 until stable readings for net leaf CO2 assimilation (An ), mesophyll intercellular CO2 concentration (Ci ), transpiration rates (E) and stomatal conductance to water vapour (gs ) were reached. We then made light response curves using neutral density filters. For each replicate plant PPFD was reduced step-wise through eight light intensities (913, 510, 273, 156, 100, 65, 26, and 3 ␮mol m−2 s−1 PPFD), with five readings logged and averaged at each light intensity once rates had stabilised. The response of An to light intensity (Q) was modelled using the quadratic equation of Prioul and Chartier (1977): An =

˚I + Amax a −



2

(˚I + Amax a ) − 4˚IkAmax a − Rd 2k

where ˚ (mol mol−1 ) is the initial slope of the light response curve or apparent quantum yield, I (␮mol m−2 s−1 PPFD) the photon flux density, Amax a (␮mol CO2 m−2 s−1 ) the light-saturated gross photosynthesis expressed on an area basis, k the convexity, and Rd (␮mol CO2 m−2 s−1 ) the dark respiration rate. Light compensation (Ic ) and light saturation (Ik ) points were modelled according to Walker (1989); all light response calculations were carried out with Photosynthesis Assistant (Dundee Scientific, Scotland, UK). After photosynthesis readings, leaf material in the chamber was excised, weighed, frozen and freeze-dried for later nutrient and pigment analysis. Chl a and b concentrations were analysed by extraction with DMF and spectrophotometric measurements according to Inskeep and Bloom (1985). We used the measured area, fresh mass (FM) and dry mass (DM) of leaves used for chlorophyll analyses to calculate the FM/DM ratio of leaf tissue, and the specific leaf area (SLA) as total leaf area per total DM of leaf biomass. Leaf carbon and nitrogen were analysed by gas chromatography after combustion of 200 ␮g triplicate subsamples in a CHN-analyser (Fisons Instruments, Model NA2000, Italy), and leaf phosphorus on 150–180 mg subsamples by inductively coupled plasmaspectrometry (Optima 2000 DV, PerkinElmer Instruments Inc., CT, USA) after digestion of ground material in HNO3 -H2 O2 in a microwave oven (Multiwave 3000, Anton Paar GmbH, Austria). 2.3. Growth and biomass allocation Each plant was harvested immediately after photosynthesis readings were completed. The polythene bags were slit lengthwise, and the substrate gently washed from the plant with care taken to avoid damaging or losing root material. Plant material was separated into roots, stems and leaves, and dried at 70 ◦ C for biomass measurements. The entire dried material of each fraction was then ground and analysed for tissue N and P content as described by Blakemore et al. (1987). We therefore had separate N and P data from the harvested plants, which were used in growth analyses, and from the leaves used in the gas exchange chamber, which were used in photosynthesis analyses. Dry masses were used for calculation of relative growth rates (ln final mass − ln initial mass/days). Unequivocal N limitation was defined as mass-based tissue N:P ratios < 13:1, as identified in numerous studies involving wetland graminoids (Güsewell, 2004). 2.4. Data analysis Relationships between nutrient uptake, gas exchange parameters and growth were analyzed by correlations and regression analysis using JMP version 8.0 (SAS Institute Inc., Cary, NC). Significant differences between regression lines were determined using ANCOVA, with species as the main factor and growth and

Fig. 1. Nutrient and pigment concentrations of leaves. (A) Phosphorus concentration vs nitrogen concentration. Bold line represents N:P ratio of 13:1. (B) Chlorophyll vs nitrogen concentration. Combined regression for the two Carex species (solid line) differs significantly (ANCOVA, F = 17.95, P = 0.02) from G. maxima (dashed line). (C) Chlorophyll a vs chlorophyll b concentration. Combined regression for the two Carex species (solid line) differs significantly (ANCOVA, F = 15.42, P = 0.006) from G. maxima (dashed line).

physiological responses as the covariate. Significant effects of species by covariate interaction identified different slopes and intercepts between species. Data were tested for homogeneity of variances before analysis using Bartlett’s test, and where necessary transformed logarithmically to meet assumptions of normality. Following Moran (2003), we report exact P values for tests rather than using Bonferroni-adjustments. Vapour pressure deficit (VPD) at light saturation was calculated from actual and saturation vapour pressures, leaf temperatures and dewpoint temperatures during the experiment. To compare the factors controlling photosynthesis, stomatal conductance and transpiration amongst the three species, we used stepwise multiple regression models to find the

40

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

Fig. 2. Relationships between the light-saturated rate of photosynthesis derived from A-Q curves and leaf nitrogen content on (A) area basis (Amax a ), (B) chlorophyll basis (Amax c ), and (C) mass basis (Amax m ). Regressions did not differ significantly between species (ANCOVA, all P > 0.10) and are therefore shown as single functions for each relationship.

combination of leaf-level variables that best explained gas exchange. Each variable was added or removed if it reduced the residual sum of squares by ≥5% or 10%, respectively. A plasticity index (PIV ) that ranges between 0 (no plasticity) and 1 (maximum plasticity) was calculated for selected leaf-level and whole-plant level traits related to success with nutrient enrichment (Valladares et al., 2006; Funk, 2008), based on (max−min)/max values but using all replicates rather than treatment means as we were interested in continuous variation. Differences in PIV between the three species were tested with one-way ANOVA for leaf-level and

Fig. 3. Variation in (A) light saturation point (Ik ), (B) leaf dark respiration rate (Rd ), and (C) maximum apparent quantum yield (˚) of the three species in relation to leaf nitrogen content. No significant regressions found for the Carex species, regressions shown for G. maxima (dashed line).

whole plant-level traits. Pearson product-moment correlation coefficients were used to test linear relationships between traits and biomass, as a measure of plant performance (Funk, 2008). 3. Results 3.1. Leaf nutrients, leaf structure and photosynthesis–nitrogen relationships Leaf nutrient concentrations varied widely in all three species, but G. maxima achieved higher concentrations of both N and P than the sedges (Fig. 1A). Leaf N:P ratios were close to 13:1 in most plants, but N-limited values < 13:1 were common in C.

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

41

Fig. 4. Variation in water relations with leaf nitrogen content. (A) Stomatal conductance (gs ), no significant regressions found for the Carex species, regression shown for G. maxima (dashed line). (B) Transpiration rate (E), significant regressions differ significantly between the Carex species (F = 4.70, P = 0.03), no significant regression for G. maxima. (C) Instantaneous water use efficiency (A/E), regressions did not differ significantly between species (ANCOVA, F = 2.06, P = 0.14) and are therefore shown as single functions for each relationship. (D) Intrinsic water use efficiency (A/gs ), no significant regressions.

virgata; in G. maxima this occurred only at high nutrient concentrations. There were strong linear relationships between leaf N and Chl content (Fig. 1B), revealing highly constant N:Chl ratios within species, which differed between the Carex spp. and G. maxima. The ratios of Chl a:b were significantly higher in G. maxima than in the Carex species, which did not differ from each other (Fig. 1C). Uniform intercepts but differing slopes in Fig. 1C indicate that Chl a:b is more similar in all three species at low nutrient availability, but greater investment in Chl a relative to Chl b progresses in G. maxima as nutrient supply increases. SLA was not affected by nutrient supply in any of the species (ANCOVA, F = 0.70, P = 0.51), but was significantly higher (ANCOVA, F = 5.18, P = 0.03) in G. maxima (17 ± 6 m2 kg−1 ) than the sedges, which did not differ from each other (C. virgata 13 ± 5 m2 kg−1 ; C. secta 14 ± 4 m2 kg−1 ). In all three species, there were strong photosynthesis–nitrogen relationships, whether expressed per unit leaf area (Amax a , Fig. 2A), leaf chlorophyll (Amax c , Fig. 2B), or leaf mass (Amax m , Fig. 2C). These relationships did not differ significantly between species, resulting in uniform photosynthesis–nitrogen relationships across all plants in the experiment, with a particularly close relationship between leaf N content and rates expressed per unit chlorophyll (Fig. 2B). However, the high SLA of G. maxima resulted in significantly higher Amax m rates than the sedges at high leaf N concentrations (Fig. 2C).

3.2. Light response parameters There was no significant relationship between leaf N content and light response parameters in the sedges, whereas both Ik and Rd increased with increasing leaf N content in G. maxima (Fig. 3A and B). Ik was lower than the sedges at all leaf N levels (Fig. 3A). At low leaf N content, Rd was similar in all three species, with increasing leaf N increasing the respiratory activity of G. maxima above the sedges. Increasing dark respiration rates (more negative y-intercepts of photosynthesis–irradiance responses) in G. maxima as N increased also resulted in a higher ˚ values, whereas ˚ was unaffected by N in the sedges (Fig. 3C). Ic (data not shown) was unaffected by leaf N (ANCOVA F = 1.29, P = 0.26) and did not differ between species (ANCOVA F = 2.58, P = 0.11). 3.3. Gas exchange, WUE and NUE The maximum gs at light saturation was not significantly related to leaf N content in the sedges, but increased with leaf N concentration in G. maxima (Fig. 4A). In contrast, E decreased at high N concentrations in the sedges, but was not significantly affected by N in G. maxima (Fig. 4B). These interactions between stomatal and transpiration behaviour resulted in a highly significant positive relationship between leaf N and the instantaneous WUE (Fig. 4C), which did not differ between species. The intrinsic WUE (A/gs )

42

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

Table 1 Multiple linear regression models describing dependence of stomatal conductance (gs ), transpiration (E) and maximum photosynthesis rates (Amax a ) on leaf morphology, nutrients and physiology.a C. virgata x

C. secta r2

P>F

x

G. maxima P>F

r2

x

P>F

r2

2.90

0.001

0.67

a

Light-saturated photosynthesis rate (Amax ) models N 1.32 0.001 0.56 gs 18.1 0.012 0.74 b Summaries 0.74 (0.70) Maximum stomatal conductance (gs ) models 0.02 0.004 VPD b

Summaries

b

VPD

3.64 7.17

0.08

0.48 (0.44)

Maximum transpiration rate (E) models −0.27 0.002 N 2.73 0.03 gs b Summaries 0.58 (0.51) a

0.48

N gs

0.0001 0.03 0.82 (0.79)

0.73 0.82

N

0.026

0.35

N Chl a:b

0.65 2.17

0.0002 0.006 0.80 (0.75)

0.52 0.80

0.69 0.73

gs VPD

0.23 0.11

0.007 0.017 0.76 (0.71)

0.49 0.76

0.67 (0.64)

0.35 (0.29) 0.37 0.58

N gs

−0.42 0.57

0.0002 0.03 0.73 (0.68)

x, parameter estimate for specified variables. Variables that did not meet the 0.05 significance level were not included in the model. Model summaries shown as partial r2 with adjusted r2 in brackets.

was not affected by N, either within species, or across the entire dataset (Fig. 4D). A/gs nevertheless differed significantly between the three species, being highest in C. virgata and lowest in G. maxima (ANCOVA F = 48.5, P ≤ 0.0007). Multiple linear regression of factors controlling photosynthesis, transpiration and stomatal conductance produced different models for G. maxima versus the sedges (Table 1). In all three species, leaf N was the most significant factor controlling Amax a , accounting for 56%, 73%, and 61% of the variation in Amax a in C. virgata, C. secta, and G. maxima respectively. However, multiple regression revealed that gs limited Amax a in the sedges, but not in G. maxima. In the sedges, VPD was the only factor explaining variation in gs , whereas in G. maxima gs was independent of VPD, instead being a function of leaf N concentration, as well as being related to Chl a:b (cf. Fig. 1C). In G. maxima, variation in E was a function of gs and VPD. In contrast, E was independent of VPD in the sedges, decreasing with leaf N content (cf. Fig. 2B), and increasing with gs . Other leaf characteristics (SLA, chlorophyll concentrations and P content) never contributed significantly to models. G. maxima allocated higher concentrations of N to leaves than shoots, especially at low nutrient supply, whereas the sedges had similar concentrations of N in both shoots and leaves (Fig. 5A). In contrast, P concentrations in leaves were similar to or lower than in shoots for all species (Fig. 5B). With increasing N content there was a decrease in C:N ratio for all plants (Fig. 5C), and the C:N ratio was lower in G. maxima than the sedges, especially at high N, indicating a lower NUE. Under excess N supply, NUE for G. maxima ranged from 20 to 23 g dry mass g−1 N, whereas in the sedges it was 1.6 times higher at 25–30 g dry mass g−1 N. Photosynthetic N use efficiency (PNUE) decreased with leaf N in all plants (Fig. 5D), with the lowest PNUE values in G. maxima.

3.4. Growth, allocation, and their relationship to gas exchange The sedges conformed to the same linear relationship between Amax a and gs , whereas G. maxima had a wider range of gs and a quadratic relationship between Amax a and gs (Fig. 6A). The relationship between gs and RGR was barely significant for the sedges, whereas for G. maxima the quadratic relationship was highly significant (Fig. 6B). The photosynthesis–growth relationship (Fig. 6C) also differed between the sedges and G. maxima, with a wider RGR range in G. maxima that was more responsive to increasing photosynthetic rate. Fig. 6C emphasises that RGR was similar for all three species at high Amax a and hence high N supply, whereas RGR was lower in G. maxima than the sedges under N-limitation at low Amax a .

Although N uptake and photosynthesis correlated with growth rates in all three species, the correlations were much stronger in G. maxima than the sedges (Table 2). In all three species Amax m correlated more strongly with growth rates and biomass than Amax a , but the strength of the correlations decreased in the order G. maxima > C. secta > C. virgata. There were also significant correlations between maximum photosynthesis rates, Rd , growth and biomass in G. maxima, but not in the sedges. N uptake was more strongly correlated with growth in G .maxima than the sedges (Table 2), and more above-ground N accumulated in G. maxima, with a curvilinear response of shoot biomass to N uptake (Fig. 7A). Although investment in shoot biomass increased with total plant N uptake in all three species (Fig. 7B), the slopes of these relationships differed, indicating less shoot investment at low N availability in G. maxima than the sedges, but similar shoot N investment at high N availability. A single relationship described the decrease in root:shoot ratio with plant size for all species, but G. maxima had a higher root:shoot ratio than the sedges in small, nutrient-limited plants (Fig. 7C), whereas root:shoot ratios were similar in all species in larger plants at high nutrient supply. Mass-based N:P ratios in shoot material ranged from 5.1 to 9.9 in C. virgata, 7.0–13.9 in C. secta, and 9.6–14.1 in G. maxima. Table 2 Pearson correlation matrices for leaf N, gas exchange parameters and RGR for the three species. Significant correlations greater than 0.6 are shown in bold. Leaf N

Amax a

Amax m

gs

DR

Carex virgata Leaf N Amax a Amax m gs Rd RGR

1 0.75 0.79 0.43 0.12 0.67

1 0.99 0.80 0.25 0.40

1 0.74 0.15 0.52

1 0.50 0.12

1 0.21

Carex secta Leaf N Amax a Amax m gs Rd RGR

1 0.85 0.40 0.33 0.10 0.83

1 0.55 0.72 0.33 0.52

1 0.57 0.44 0.65

1 0.05 0.13

1 0.33

Glyceria maxima 1 Leaf N 0.82 Amax a m 0.48 Amax 0.51 gs 0.61 Rd 0.94 RGR

1 0.88 0.52 0.74 0.62

1 0.23 0.61 0.90

1 0.23 0.57

1 0.67

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

43

Fig. 5. Comparison of shoot and leaf concentrations of (A) nitrogen and (B) phosphorus, and leaf N concentration and (C) the C:N ratio (growth NUE) and (D) PNUE. Bold lines indicate 1:1 ratio.

3.5. Trait plasticity All of the traits used in plasticity analyses showed moderate to large plasticity in the three species, apart from SLA and Chl a:b (Table 3). G. maxima did not, however, exhibit higher plasticity for most leaf-level traits, and at the leaf level did not show significantly higher trait plasticity overall than the sedges. Of these traits, only gs and A/gs had higher PIV values in G. maxima than the sedges. In contrast, the whole plant-level traits were generally more plastic than the leaf-level traits, and were significantly more plastic overall in G. maxima than the sedges. More plastic allocation between above- and below-ground biomass was particularly evident in G. maxima. Most traits correlated strongly with total biomass in all three species, including both those that did and did not differ in plasticity between species, and whole-plant traits generally correlated more strongly than leaf-level traits. In G. maxima, correlations with biomass were much stronger for almost all the traits in Table 3 compared to the sedges. 4. Discussion Contrary to the first hypothesis of our study, G. maxima did not have higher growth rates under excess nutrient supply than the sedges, nor was its photosynthesis on an area basis (Amax a ) higher. This is in contrast to a number of previous studies from both terrestrial and wetland environments that found higher growth and photosynthesis rates in invaders than their native

competitors (Feng et al., 2009; Jiang et al., 2009). However, excess nitrogen did produce higher mass-based rates (Amax m ) in G. maxima than the Carex species, and mass-based photosynthetic rates often correlate better with growth and productivity than areabased rates (Poorter et al., 1990), which was the case for G. maxima but not the sedges. Higher Amax m in G. maxima was largely a function of higher SLA, consistent with suggestions that high SLA is itself associated with fast-growing, competitive species, as thinner leaves have lower light attenuation and higher mesophyll conductance to CO2 , increasing photosynthesis over a range of light intensities compared to thicker leaves (Reich et al., 1998). Although SLA is often strongly correlated to N supply due to changes in water and starch content (Garnier et al., 1997; Knops and Reinhart, 2000), it was unaffected by N in our species. The consistently higher SLA of G. maxima compared to Carex species fits previous observations that species with low SLA (long leaf lifespan, resistant to grazing, low leaf N) dominate lower-N habitats, being replaced by species with high SLA (short leaf lifespan, more readily grazed, high leaf N) as N increases (Elberse and Berendse, 1993). The extremely strong regressions between leaf N and photosynthesis rates in our data are consistent with all three species investing N heavily into active Rubisco, chlorophyll and other photosynthetic proteins (Shipley et al., 2005), rather than organic compounds involved in nutrient conservation under infertile conditions. However, high photosynthetic rates are not necessarily associated with high growth rates, as carbon assimilation supports maintenance and storage processes as well as growth, and

44

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

Table 3 The plasticity index (PIV ) for leaf-level and plant-level traits of the three species across all treatmentsa , and Pearson product-moment correlation coefficients (r) for relationships between traits and total biomass (n = 15). PIV

Leaf level traits Amax a Amax m PNUE Leaf Na Leaf Nm Chl a/b Chl/N A/E gs A/gs SLA a

Mean (SD)

Whole-plant traits N content NUE P content RGR Root:shoot Root mass ratio Leaf mass ratio a a * ** ***

Mean (SD)

Biomass relationship

C. virgata

C. secta

G. maxima

0.43 0.47 0.59 0.66 0.68 0.35 0.35 0.54 0.56 0.39 0.63

0.43 0.28 0.58 0.67 0.59 0.20 0.38 0.47 0.48 0.54 0.76

0.47 0.37 0.54 0.66 0.60 0.22 0.26 0.52 0.83 0.74 0.76

0.52 (0.14)

0.49 (0.17)

0.54 (0.23)

0.63 0.45 0.68 0.40 0.89 0.72 0.54

0.67 0.67 0.75 0.36 0.77 0.58 0.41

0.69 0.69 0.93 0.67 0.93 0.79 0.66

0.61 (0.17)

0.60 (0.16)

0.76 (0.12)

C. virgata

C. secta

G. maxima

0.54* −0.56* 0.70** 0.72**

0.54* 0.66* −0.53* 0.69** 0.67**

0.51* 0.83*** −0.75* 0.97*** 0.98***

0.66** 0.71**

0.75** 0.71** 0.81*** 0.97*** −0.82*** −0.84*** 0.85***

0.52* 0.85***

0.88*** 0.79*** 0.73** 0.98*** −0.54** −0.51** 0.51**

0.69** 0.75** −0.68*

0.94*** 0.87*** 0.92*** 0.97*** −0.93*** −0.95*** 0.94***

Mean PIV compared between the three species by one-way ANOVA for gas exchange traits (F2,32 = 0.29, P = 0.75) and whole-plant traits (F2,23 = 2.68, P < 0.05). P < 0.05. P < 0.01. P < 0.001.

biometric allocation and biomass losses are often more important in determining productivity (Körner, 1991). Instead, the degree of physiological integration between nitrogen allocation, photosynthesis, respiration and carbon allocation may be a better predictor of growth and biomass than photosynthetic activity per se, and it is notable in our study that correlations between photosynthesis, respiration and growth were much stronger in G. maxima than the sedges. This tighter physiological integration, notably involving an increase in dark respiration at higher N in G. maxima and therefore more energy for growth, indicates that this species’ strategy is to prioritise rapid growth in response to N addition, whereas the sedges are allocating more of their photosynthate to other functions such as storage. Increases in N availability usually increase growth but reduce plant allocation to below-ground biomass and increase N partitioning to leaves (Suding et al., 2005), which was the basis of our second hypothesis, that this would be more pronounced in G. maxima than the natives. This was supported by the differences in growth and allocation we observed, but of particular note is the similarity in RGR and allocation at high nutrient supply in all three species, and that it was at low nutrient supply that greatest differences occurred (i.e. G. maxima having much lower RGR than the sedges and having less below-ground allocation). G. maxima did not perform better than the sedges under high nutrients; rather, it performed more poorly under low nutrients. Although some environments feature invasive species that compete successfully under low nutrient availability (e.g. Laungani and Knops, 2009), our study supports the concept that plant invasions in freshwater wetlands are strongly linked to nutrient enrichment (Zedler and Kercher, 2004), and hence that reduction in anthropogenic eutrophication is a critical strategy for protecting wetlands from weed invasion. The range of N:P ratios in our data and absence of P as a significant factor in our models supports the general principle that N, rather than P, is the important growth-limiting nutrient that needs to be

managed in eutrophication problems in most freshwater swamps and marshes (Güsewell, 2004; Ket et al., 2011). Growth and allocation patterns also support our third hypothesis, that G. maxima would show greater phenotypic plasticity than the sedges. Whilst there was relatively little phenotypic plasticity in photosynthetic and leaf-level parameters, as these are usually constrained within relatively narrow variation, the much greater plasticity of parameters such as RGR, root:shoot ratio and LWR in G. maxima than the sedges is consistent with the principle that plasticity in such features is likely to assist invaders to establish in novel environments, and take advantage of fluctuating resources to outcompete existing vegetation (Davidson et al., 2011). Moreover, the stronger correlation of RGR, root:shoot ratio and LWR to biomass in G. maxima than the sedges supports the importance of these traits in fitness and invasion success, at least when using biomass as a proxy for fitness in short-term growth experiments (Funk, 2008). An assessment of fitness parameters such as fecundity and reproductive output is often needed to fully assess invasiveness, but G. maxima produces little viable seed in most of its range (Lambert, 1947; Anderson and Reznicek, 1994), so biomass resulting from clonal reproduction is probably the most valid assessment of its fitness. Biomass is also a useful fitness proxy because greater vegetative size is often associated with higher reproductive output (Weiner et al., 2009), and successful invaders must eventually accrue significantly more biomass than their native competitors (McKinley and Blair, 2008). Although the clonal material used in our experiment was collected from a single site and probably was genetically uniform, it nevertheless showed greater plasticity than the seed-germinated sedges, which could be expected to be more genetically diverse. Any G. maxima populations with viable seed may potentially be even more plastic than New Zealand material, which very rarely seeds, but it is difficult to predict whether this would translate into any greater invasiveness.

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

Fig. 6. Relationships of stomatal conductance (gs ) at light saturation to (A) Amax a (combined regression for the two Carex species (solid line) differs significantly from G. maxima (dashed line), ANCOVA, F =3.89, P = 0.02), and to (B) the relative growth rate of the three species (combined regression for the two Carex species (solid line) differs significantly from G. maxima (dashed line), ANCOVA, F =7.33, P = 0.006). (C) The relationship of Amax a to relative growth rate (combined regressions for the two Carex species (solid line) differ significantly from G. maxima (dashed line), ANCOVA, F = 5.90, P = 0.004).

For invasion success in eutrophicated wetland environments, nutrient stimulation of growth is likely to interact with other factors such as light and water availability. The lower Ik for G. maxima compared to the sedges, most probably due to its thinner leaves, may contribute to the success of clonal shoots exploring and invading shade environments (Xu et al., 2010) such as under the tall tussock growth-forms of these sedges. Its higher Chl a:b at high N nevertheless indicates that it may also compete well under high light intensities. The very high gs in G. maxima may be particularly relevant to its competitive success over longer time frames than our experiment, as a high gs is frequently associated with high primary productivity under well-watered conditions, maximising

45

Fig. 7. Relationship between nitrogen uptake and biomass allocation. (A) Shoot biomass as a function of N in above-ground biomass. (B) Shoot fraction of biomass as a function of total plant nitrogen concentration; regressions for the two Carex species (solid line) differ significantly from G. maxima (dashed line), ANCOVA, F = 4.77, P = 0.007. (C) Root:shoot ratio as a function of total plant biomass.

water and thereby N uptake (Lu et al., 1998), and CO2 flux to the mesophyll (Farquhar et al., 1980). In terrestrial environments there is a trade-off between WUE and NUE because higher gs increases Ci and PNUE while reducing WUE (Field et al., 1983; Lambers et al., 2008), but in wetlands high water availability means that low WUE is not a disadvantage at high fertility. A species like G. maxima with a very low intrinsic WUE (A/gs ) will therefore be highly competitive in eutrophicated wetlands, as excess uptake of water and nutrients provides the resources that allow the growth plasticity to be expressed more than in species like the Carex sedges, which have more conservative stomatal physiology and N uptake limitation.

46

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47

The favouring of G. maxima by excess nutrient supply has parallels with other invasive grasses in wetlands such as Phalaris arundinacea L., which behaves similarly (Kercher and Zedler, 2004). Exploiting excess resource availability is a particularly useful strategy for wetland weeds, because runoff patterns into wetlands often produce episodic flushes of nutrients, sediment deposition and scouring, providing opportunities for colonisation by fast-growing nutrient-demanding species such as G. maxima, P. arundinacea, and Typha spp. (Smith and Newman, 2001; Zedler and Kercher, 2004). An additional feature of species likely to be invasive in these environments is high anoxia tolerance, as nutrient-rich sediments in wetlands are strongly anaerobic, and this is true not only for P. arundinacea and Typha (Kercher and Zedler, 2004), but also G. maxima, which is highly aerenchymatous and efficiently aerates its roots (Bodelier et al., 1998). In relation to our original research questions, our results show that G. maxima has several growth-related ecophysiological advantages over Carex sedges, including a higher SLA, and closer linkages between photosynthesis, respiration and growth, but it does not have inherently higher growth rates. Rather, like many other invasive species, it shows greater plasticity of its growth response to nutrient enrichment. Its low WUE and low NUE not being disadvantageous when both water and nutrients are present in excess, together with its high plasticity, are likely to be the important features of its success under eutrophication in wetlands. Furthermore, its poor competitiveness at low fertility emphasises the value of nutrient management, especially reduction in N loading, as a strategy to reduce the impact of invasive species in wetland environments. Acknowledgements This study was funded by the New Zealand Ministry of Science and Innovation (Contract C09X1002) and the Danish Council for Independent Research – Natural Sciences (Project Number 272-070633). We thank the staff of the Silverstream Research Facility for assistance in caring for plants and maintaining the experiment. References Anderson, J.E., Reznicek, A.A., 1994. Glyceria maxima (Poaceae) in New England. Rhodora 96, 97–101. Blakemore, L.C., Searle, P.L., Daly, B.K., 1987. Methods for chemical analysis of soils. New Zealand Soil Bureau Scientific Report 80. Department of Scientific and Industrial Research, Lower Hutt, NZ. Bodelier, P.L.E., Duyts, H., Blom, C.W.P.M., Laanbroek, H.J., 1998. Interactions between nitrifying and denitrifying bacteria in gnotobiotic microcosms planted with the emergent macrophyte Glyceria maxima. FEMS Microbiology and Ecology 25, 63–78. Champion, P.D., Clayton, J.S., Rowe, D.K., 2002. Alien Invaders. Lake Managers’ Handbook. Ministry for the Environment, Wellington, NZ. Childers, D.L., 2006. A synthesis of long-term research by the Florida Coastal Everglades LTER Program. Hydrobiologia 569, 531–544. Clarke, A., Lake, P.S., O’Dowd, D., 2004. Ecological impacts on aquatic macroinvertebrates following upland stream invasion by a ponded pasture grass (Glyceria maxima) in southern Australia. Marine and Freshwater Research 55, 709–713. Davidson, A.M., Jennions, M., Nicotra, A.B., 2011. Do invasive species show higher phenotypic plasticity than native species and, if so, is it adaptive? A metaanalysis. Ecology Letters 14, 419–431. Durand, L.Z., Goldstein, G., 2001. Photosynthesis, photoinhibition, and nitrogen use efficiency in native and invasive tree ferns in Hawaii. Oecologia 126, 345–354. Ehrenfeld, J.G., 2008. Exotic invasive species in urban wetlands: environmental correlates and implications for wetland management. Journal of Applied Ecology 45, 1160–1169. Elberse, W.T., Berendse, F., 1993. A comparative study of the growth and morphology of eight grass species from habitats with different nutrient availabilities. Functional Ecology 7, 223–229. Evans, J.R., Poorter, H., 2001. Photosynthetic acclimation of plants to growth irradiance: the relative importance of specific leaf area and nitrogen partitioning in maximizing carbon gain. Plant, Cell & Environment 24, 755–767. Farnsworth, E.J., Meyerson, L.A., 2003. Comparative ecophysiology of four wetland plant species along a continuum of invasiveness. Wetlands 23, 750–762. Farquhar, G.D., Schulze, E.-D., Küppers, M., 1980. Responses to humidity by stomata of Nicotiana glauca L. and Corylus avellana L. are consistent with the optimization

of carbon dioxide uptake with respect to water loss. Australian Journal of Plant Physiology 7, 315–327. Faulkner, S.P., Patrick, W.H., Gambrell, R.P., 1989. Field techniques for measuring wetland soil parameters. Soil Science Society of America Journal 53, 883–890. Feng, Y.-L., Lei, Y.-B., Wang, R.-F., Callaway, R.M., Valiente-Banuet, A., Inderjit Li, Y.-P., Zheng, Y.-L., 2009. Evolutionary tradeoffs for nitrogen allocation to photosynthesis versus cell walls in an invasive plant. Proceedings of the National Academy of Sciences of the United States of America 106, 1853–1856. Field, C., Merino, J., Mooney, H.A., 1983. Compromises between water-use efficiency and nitrogen-use efficiency in five species of California evergreens. Oecologia 60, 384–389. Funk, J.L., 2008. Differences in plasticity between invasive and native plants from a low resource environment. Journal of Ecology 96, 1162–1173. Garnier, E., Cordonnier, P., Guillerm, J.-L., Sonié, L., 1997. Specific leaf area and leaf nitrogen concentration in annual and perennial grass species growing in Mediterranean old-fields. Oecologia 111, 490–498. Güsewell, S., 2004. N:P ratios in terrestrial plants: variation and functional significance. New Phytologist 164, 243–266. Inskeep, W.P., Bloom, P.R., 1985. Extinction coefficients of chlorophyll a and b in N,N-dimethylformamide and 80% acetone. Plant Physiology 77, 483–485. Jiang, L.-F., Luo, Y.-Q., Chen, J.-K., Li, B., 2009. Ecophysiological characteristics of invasive Spartina alterniflora and native species in salt marshes of Yangtze River estuary China. Estuarine Coastal Shelf Science 81, 74–82. Johnson, P.N., Gerbeaux, P.J., 2004. Wetland Types in New Zealand. Department of Conservation, Wellington, NZ. Keddy, P.A., 2005. Putting the plants back into plant ecology: six pragmatic models for understanding and conserving plant diversity. Annals of Botany 96, 177–189. Keddy, P.A., 2010. Wetland Ecology: Principles and Conservation, 2nd edition. Cambridge University Press, Cambridge, UK. Kercher, S.M., Zedler, J.B., 2004. Flood tolerance in wetland angiosperms: a comparison of invasive and noninvasive species. Aquatic Botany 80, 89–102. Ket, W.A., Schubauer-Bergen, J.P., Craft, C.B., 2011. Effects of five years of nitrogen and phosphorus additions on a Zizaniopsis miliacea tidal freshwater marsh. Aquatic Botany 95, 17–23. Knops, J.M.H., Reinhart, K., 2000. Specific leaf area along a nitrogen fertilization gradient. American Midland Naturalist 144, 265–272. Körner, C., 1991. Some often overlooked plant characteristics as determinants of plant growth: a reconsideration. Functional Ecology 5, 162–173. Lambers, H., Chapin, F.S., Pons, T.L., 2008. Plant Physiological Ecology, 2nd edition. Springer, New York, USA. Lambert, J.M., 1947. Glyceria maxima (Hartm.) Holmb. Journal of Ecology 34, 310–344. Laungani, R., Knops, J.M.H., 2009. Species-driven changes in nitrogen cycling can provide a mechanism for plant invasions. Proceedings of the National Academy of Sciences of the United States of America 106, 12400–12405. Li, S., Mendelssohn, I.A., Chen, H., Orem, W.H., 2009. Does sulphate enrichment promote the expansion of Typha domingensis (cattail) in the Florida Everglades? Freshwater Biology 54, 1909–1923. Loo, S.E., MacNally, R., O’Dowd, D., Thomson, J.R., Lake, P.S., 2009. Multiple scale analysis of factors influencing the distribution of an invasive aquatic grass. Biological Invasions 11, 1903–1912. Lu, Z., Percy, R.G., Qualset, C.O., Zeiger, E., 1998. Stomatal conductance predicts yields in irrigated Pima cotton and bread wheat grown at high temperatures. Journal of Experimental Botany 49, 453–460. Mal, T.K., Lovett-Doust, J., 2005. Phenotypic plasticity in vegetative and reproductive traits in an invasive weed, Lythrum salicaria (Lythraceae), in response to soil moisture. American Journal of Botany 92, 819–825. McConnaughay, K.D.M., Coleman, J.S., 1999. Biomass allocation in plants: ontogeny or optimality? A test along three resource gradients. Ecology 80, 2581–2593. McKinley, D.C., Blair, J.M., 2008. Woody plant encroachment by Juniperus virginiana in a semiarid native grassland promotes rapid carbon and nitrogen accrual. Ecosystems 11, 454–468. Moran, M.D., 2003. Arguments for rejecting the sequential Bonferroni in ecological studies. Oikos 100, 403–405. Munzarová, E., Lorenzen, B., Brix, H., Vojtisková, L., Votrubová, O., 2005. Effect of NH4 + /NO3 − availability on nitrate reductase activity and nitrogen accumulation in wetland helophytes Phragmites australis and Glyceria maxima. Aquatic Botany 55, 49–60. Nurminen, L., 2003. Macrophyte species composition reflecting water quality changes in adjacent water bodies of Lake Hiidenvesi, SW Finland. Annales Botanici Fennici 40, 199–208. Parker, I.M., Simberloff, D., Lonsdale, W.M., Goodell, K., Wonham, M., Kareiva, P.M., Williamson, M.H., Von Holle, B., Moyle, P.B., Byers, J.E., Goldwasser, L., 1999. Impact: toward a framework for understanding the ecological effects of invaders. Biological Invasions 1, 3–19. Poorter, H., Remkes, C., Lambers, H., 1990. Carbon and nitrogen economy of 24 wild species differing in relative growth rate. Plant Physiology 94, 621–627. Prioul, J.L., Chartier, P., 1977. Partitioning of transfer and carboxylation components of intercellular resistance to photosynthetic CO2 fixation: a critical analysis of the method used. Annals of Botany 41, 789–800. Pyˇsek, P., Richardson, D.M., 2007. Traits associated with invasiveness in alien plants: where do we stand? In: Nentwig, W. (Ed.), Ecological Studies. Springer-Verlag, Berlin, pp. 97–125. Reich, P.B., Ellsworth, D.S., Walters, M.B., 1998. Leaf structure (specific leaf area) modulates photosynthesis–nitrogen relations: evidence from within and across species and functional groups. Functional Ecology 12, 948–958.

B.K. Sorrell et al. / Aquatic Botany 103 (2012) 37–47 Shipley, B., Vile, D., Garnier, E., Wright, I.J., Poorter, H., 2005. Functional linkages between leaf traits and net photosynthetic rate: reconciling empirical and mechanistic models. Functional Ecology 19, 602–615. Simberloff, D., 2004. Community ecology: is it time to move on? The American Naturalist 163, 787–799. Smith, S.M., Newman, S., 2001. Growth of southern cattail (Typha domingensis Pers.) in response to fire-related soil conditions in a northern Everglades marsh. Wetlands 21, 363–369. Suding, K.N., Collins, S.L., Gough, L., Clark, C., Cleland, E.E., Gross, K.L., et al., 2005. Functional- and abundance-based mechanisms explain diversity loss due to N fertilization. Proceedings of the National Academy of Sciences of the United States of America 102, 4387–4392. Sugiharto, B., Miyata, K., Nakamoto, H., Sasakawa, H., Sugiyama, T., 1990. Regulation of expression of carbon-assimilating enzymes by nitrogen in maize leaf. Plant Physiology 92, 963–969. Valladares, F., Sanchez-Gomez, D., Zavala, M.A., 2006. Quantitative estimation of phenotypic plasticity: bridging the gap between the evolutionary concept and its ecological applications. Journal of Ecology 94, 1103–1116.

47

Walker, D.A., 1989. Automated measurement of leaf photosynthetic O2 evolution as a function of photon flux density. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 323, 313–326. Wei, A., Chow-Fraser, P., 2006. Synergistic impact of water level fluctuation and invasion of Glyceria on Typha in a freshwater marsh of Lake Ontario. Aquatic Botany 84, 63–69. Weiner, J., Campbell, L., Pino, J., Echarte, L., 2009. The allometry of reproduction within plant populations. Journal of Ecology 97, 1220–1233. Xu, C.-Y., Schooler, S.S., van Klinken, R.D., 2010. Effects of clonal integration and light availability on the growth and physiology of two invasive herbs. Journal of Ecology 98, 833–844. Zedler, J.B., Kercher, S., 2004. Causes and consequences of invasive plants in wetlands: opportunities, opportunists, and outcomes. Critical Reviews in Plant Sciences 23, 431–452.