Seasonal Variation of Leaf Ecophysiological Traits of Iris Variegata Observed in Two Consecutive Years in Natural Habitats with Contrasting Light Conditions

Arch. Biol. Sci., Belgrade, 67(4), 1227-1236, 2015 DOI:10.2298/ABS150311099Z

Seasonal variation of leaf ecophysiological traits of Iris variegata observed in two consecutive years in natural habitats with contrasting light conditions

Uroš Živković, Danijela Miljković, Nataša Barišić Klisarić, Aleksej Tarasjev and Stevan Avramov*

Institute for Biological Research “Siniša Stanković”, University of Belgrade, Belgrade, Serbia

*Corresponding author: [email protected]

Abstract: The amount and pattern of individual phenotypic responses to seasonal changes in environmental conditions were determined in clones of Iris variegata growing in differing light habitats. For the purpose of the study, 97 clonal plants of the rhizomatous herb I. variegata that experienced different light conditions in their two native habitats were selected: one along the top and slope of sand dunes and one in woodland understories. Two fully expanded leaves that had developed during spring, summer and fall in two consecutive years were sampled from each of these clones. Six leaf traits affecting the photosynthetic rate of a plant − morphological (specific leaf area), anatomical (stomatal density) and physiological (total chlorophyll concentration, chlorophyll a/chlorophyll b ratio, carotenoid concentration, chlorophyll a/carotenoid ratio) exhibited significant plastic responses in the two different light habitats. To test whether these traits differ between exposed and shaded habitats as well as during different vegetation periods, we used the repeated model analysis of variance (ANOVA). Results of the repeated ANOVA revealed statistically significant effects of year, habitat and period of vegetation season. Patterns of changes during growing seasons were year-specific for almost all analyzed traits.

Key words: light conditions; seasonal change; I. variegata; ecophysiological traits; Deliblato Sands

Received: March 11, 2015; Revised: April 09, 2015; Accepted: April 14, 2015

INTRODUCTION put (Halliday et al., 1994; Tarasjev, 1997; Valladares and Pearcy, 1998; Poorter, 2001; Mattson and Erwin, Plants, due to their sedentary life form, during their 2005; Avramov et al., 2007; Tarasjev et al., 2009). Di- evolutionary process develop a set of mechanisms to vergence in the aforementioned traits may originate adapt to varying environmental conditions, which from genetic differences among populations as well results in highly diversified phenotypes. A change in as from differences in environmental conditions be- the average phenotype expressed by a single geno- tween habitats. type in different environments is generally considered a phenotypic plasticity (Bradshaw, 1965; Gratani, The evolution of adaptation depends not only on 2014). Because of highly variable environmental con- the genetic variation that leads to between-population ditions, substantial phenotypic variation can be ob- differentiation for the traits in question, but also on served on different plant traits. In order to properly their phenotypic plasticity that can lead to emergence understand plant responses, multiple and interacting of the same phenomenon (Schlichting and Pigliucci, factors have to be analyzed on several output levels. 1998; Pigliucci, 2001; de Jong, 2005). Since morpho- Ecologically important developmental responses logical plasticity in leaf size may reflect underlying of plants to changing conditions are numerous and anatomical and physiological changes and because the include specific adjustments in all aspects of their magnitude and the direction of plasticity to the envi- phenotype: morphology, anatomy and physiology, as ronment can differ among congeneric species (Sultan, well as in flowering phenology and reproductive out- 2003), or conspecific populations (Pemac and Tucić,

1227 1228 Živković et al.

1998) with different environmental distributions, it forms of trait variability in response to environmental seems important to examine which component of leaf heterogeneity. phenotype is the most significant for plastic adjust- ment to ambient conditions that significantly change In order to fulfill those objectives we addressed through vegetative season (Valladares, 2012; Ferreira, the following: (i) how did the monitored ecophysi- 2013; Ballare, 2014). ological traits chang during vegetational seasons; (ii) whether genotypes originating from different light For plants, light is one of crucial environmental habitats differ in patterns of changes during seasons, factors because it provides energy for photosynthesis and (iii) whether the mode of change is the same or and controls growth and development. Under subop- different during two successive years? timal irradiance conditions, plastic changes occur at the level of individual leaves. They include different modifications in leaf structure and physiology, which MATERIALS AND METHODS lead to a specific leaf display commonly named “shade leaves” (Lichtenthaler, 1996; Ruberti, 2012; Ciolfi, Iris variegata L. (Hungarian, variegated or multicol- 2013). Shade leaves have a larger leaf area, a reduced ored iris) inhabits areas of central and southeastern stomatal density, are thinner and possess a smaller Europe. It can be found in Germany, southern Czech sclerenchyma size and vascular bundle number, and Republic, Austria, southern Slovakia, Hungary, west- a lower light saturation point of the overall photo- ern Ukraine, Bulgaria, southern Romania and north- synthesis compared to leaves exposed to full sunlight ern Serbia. I. variegata inhabits grassy and open forest (Bjorkman, 1981; Lichtenthaler, 1996; Cao and Booth, habitats. Since its natural habitats differ in a num- 2001; Avramov et al., 2007). Since photosynthesis, and ber of environmental parameters, most prominent is therefore plant growth, directly depends on the level of the divergence in quality and intensity of light, and available solar energy, a shade-elicited increase in the therefore habitats can generally be divided into open size of light-capturing leaf area effectively compensates habitats where plants are exposed to full sunlight, and for the inevitable reduction in photosynthetic rate in shaded habitats, such as the ground floor of different light deprived environments (Wild and Wolf, 1980; forest stands with a reduced intensity and changed Sultan and Bazzaz, 1993; Nicotra et al., 1997; Tucić et quality of the light. al., 1998; Oguchi et al., 2003). Two groups of genotypes of Iris variegata inhabit- The objective of this study was to quantify the ing contrasting light conditions in the dune system relationship between the phenotypic characteristics at Deliblato Sands (44°48’ N, 38°58’ E, Serbia) were of genotypes/clones of Iris variegata and their growth selected for this study. The first group of genotypes conditions through comparison of the amount and (“Open”) occupied exposed areas on the dunes cov- pattern of phenotypic responses to seasonal changes ered with annual and perennial herbs and low shrubs, in environmental conditions. Three characters that while the second group of genotypes (“Shaded”) was directly affect the photosynthetic rate of an indi- situated in the understories of different forest stands. vidual were analyzed: specific leaf area (SLA), which These habitats are very different in terms of light influences light energy interception, stomatal density, intensity, soil characteristics and vegetation cover; which controls gaseous exchange, and chlorophyll nonetheless, natural growing clones were present in and carotenoids concentrations, which act as indica- both. The estimated mean values for daily photosyn- tors of plant stress. In this paper, we analyzed plastic thetic active radiation (PAR) and red:far-red (R:FR) response to seasonal changes of environmental factors light ratio in these habitats, under clear sky condi- in two successive years. The focus was also on the de- tions, were 1173.1 μmol m–2 s–1; R:FR = 1.025 at the termination of the suitability of Iris variegata for more exposed dune site and 128.36 μmol m–2 s–1; R:FR = detailed research in the course of the aforementioned 0.78 under the canopy, respectively. Variation of leaf traits of Iris variegata 1229

Forty-seven clonal plants from the open and 50 were analyzed using a repeated-measures analysis of from the shaded habitat were randomly selected, variance (REPEATED option in SAS GLM procedure; marked and leaves were taken for analysis in May, SAS Institute, 2011). In our experimental model, year July and September of 2012 and in the same periods and habitat were defined as classification variables. of 2013. In this approach, each repeated measure of a trait on the same individual is treated as a dependent variable. In order to assess the plant response to different According to measures terminology, the measured light conditions, the following quantitative traits were individuals are referred to as subjects, the repeated measured: (1) stomatal density (SD; number of stoma- observations on each individual as the within-subject ta/μm2); (2) specific leaf area (SLA; leaf area/leaf mass, or repeated factor, and the habitats from which the cm2/g); (3) total chlorophyll concentration (ChlT; subjects originated and the experimental treatments mg/g); (4) the ratio of chlorophyll a to chlorophyll b to which they were exposed as the between-subject (Chla/b); (5) carotenoid concentration (Car; mg/g) and factor. In this particular experiment, the Year and the (6) the ratio of chlorophyll a to carotenoids (Chla/Car). Habitat would be considered as the between-subject Specific leaf area was determined as the ratio of factors, while the Season, the Season x Year and the leaf surface area and dry leaf biomass (48 h at 60ºC) Season x Habitat interaction would be considered as using the last fully developed leaf. Stomatal density within-subject factors. was estimated by applying a microrelief method (Pa- zourek, 1970). For slide preparation, each leaf was The pattern of response of the within-subject painted across the middle of its surface with a 0.5cm- factor (Season) was analyzed using the profile analy- wide band of clear nail polish over the entire width, sis (REPEATED/PROFILE option in the SAS GLM in a direction perpendicular to the longer axis of its procedure; SAS Institute, 2011), which transforms blade. After allowing it to dry, the dry polish copy of the within-subject repeated observations to a set of the leaf surface was peeled off with a piece of trans- differences (contrast) and then makes the univariate parent adhesive tape and mounted on a microscope analyses on the contrast. The results of a profile analy- slide. Stomatal counts were made in 10 randomly sis of the within-subject data show whether there are chosen microscopic fields (X40 magnification) on significant changes in trait values in the following each microscope slide per leaf. time intervals: between spring and summer, summer and fall, and spring and fall. Total chlorophyll concentration was estimated according to Hiscox and Israelstam (1979). Chloro- phyll extracts were prepared using the upper half of RESULTS the second fully developed leaf. An average of 10-15 mg of leaf tissue were placed in a vial containing 1 mL In the sampled clones growing in different habitats, of DMSO (dimethyl sulfoxide) and incubated for 6 h all analyzed traits were affected by prevailing light at 65ºC. After incubation, chlorophyll and carotenoid conditions. Seasonal changes in the analyzed traits absorptions were measured at wavelengths of 665, 649 are displayed in the results of repeated model analy- nm and 480 nm, using a Multiscan Spectrum v1.2. sis (ANOVA) and PROFILE analysis (Tables 1 and 2). While genotypes from light habitats did not show To estimate phenotypic variability of several leaf different patterns of change across seasons, the mode traits in Iris variegata in the environmental conditions of change during two successive years was clearly dif- of its natural habitats during spring, summer and fall, ferent (Figs. 1 and 2). analysis of variance was applied. Since the experimental measurements of the same traits were repeated on There was a general tendency for stomatal density each clonal individual over time (from the beginning to decrease from spring to summer and to increase until the end of the vegetation period), obtained data from summer to fall in genotypes from both open and 1230 Živković et al.

Table 1. Repeated model analysis of variance (ANOVA) and PROFILE analysis for three Iris variegata leaf traits (stomatal density; specific leaf area; total chlorophyll concentration) in genotypes from contrasting light habitats observed across seasons (spring, summer, fall) in two consecutive years. Source of variation Stomatal density Specific leaf area Total chlorophyll conc. Between-subject df MS F MS F MS F Year 1 731.86 13.95*** 2.85 32.94**** 3506.33 1.06 Habitat 1 1000.92 19.10**** 5.49 63.60**** 122129.05 36.98**** error 143 52.47 0.09 3302.24 Within-subject Season 2 71360.46 1611.54**** 1.48 35.57**** 12144718.84 3697.44**** Season x Year 2 737.96 16.67**** 2.26 55.46**** 2896.31 0.88 Season x Habitat 2 549.21 12.40**** 0.24 5.92** 104780.28 31.90**** error 286 44.28 0.04 3284.63 Profile analysis Spring-Summer 1 210711.46 1607.79**** 5.78 57.52**** 36514265.19 3722.77**** Summer-Fall 1 217399.04 1632.00**** 2.34 22.69**** 176.52 15.52**** Spring-Fall 1 52.23 36.83**** 0.76 17.14**** 36353871.31 3676.54**** *P <0.05; ** P <0.01; *** P <0.001; **** P <0.0001. shaded habitats in the first observed year. A some- (Table 1). In order to identify a particular time-inter- what different pattern was detected in the following val in which the within-subject effects were different, year, showing a continuous decrease in the same trait profile analyses were computed for each of three con- values through three seasons (Fig. 1). trasts: spring-summer; summer-fall and spring-fall. In all three time-intervals there was significant mean By observing all seasons, the mean stomatal den- effect (P<0.0001), which clearly shows that there were sities differed between two years (significant year- significant differences in the mean stomatal density effect in ANOVA, P=0.0003, Table 1). Similar results between all three seasons (Table 1). The mean SLAs were registered when stomatal density were compared differ between the two years (P<0.0001). Similar re- between clones from different light habitats (habitat sults were obtained when SLAs were compared be- effect, P<0.0001, Table 1). Genotypes from the open tween genotypes occurring in differently lit habitats habitat had significantly higher values of stomatal (significant habitat effect, P<0.0001) (Table 1). Geno- densities compared to the shaded habitat (Fig. 1). types from the open habitat had significantly lower The results of ANOVA on the differences of con- values of SLA in all three seasons and in both years secutive seasons revealed a statistically significant (Fig. 1). The repeated ANOVA of the specific leaf season effect (P<0.0001) indicating that the mean area between seasons revealed a statistically signifi- stomatal density significantly changed over seasons. cant season effect (P<0.0001), indicating significant Since the season x year interaction was also signifi- change in the mean values of SLA through different cant (P<0.0001), it suggests that the ways in which parts of the vegetation periods. The mean response stomatal density changed between the seasons were curves of the levels of the between-subject factors not the same in successive years (Table 1). (year and habitat) revealed statistically significant season x habitat interaction (P=0.0030) as well as season Significant season x habitat interaction indicates x year interaction (P<0.0001). The first-mentioned that the stomatal densities of genotypes originating interaction testifies that SLA values change in rather from different habitats changed in different ways different ways in genotypes from different habitats during the three seasons within the year (P<0.0001) through all seasons. The time x year interaction Variation of leaf traits of Iris variegata 1231

values of ChlT for genotypes originating from different habitats through all seasons. Season x year interaction was not statistically significant (Table 1). Individual ANOVAs computed on each of the three contrast variables (spring-summer; summer- fall and spring-fall) showed a significant mean effect (P<0.0001), which indicates that the change rates of total chlorophyll concentration were significantly different across seasons (Table 1). One of the important features of plant stress physiology beside total chlorophyll concentration is chlorophyll a/b ratio. When comparing overall mean values of chlorophyll a/b ratio, it was clearly shown that the mentioned concentrations were significantly higher in the shaded than in the open habitats (habitat effect, P<0.0001, Table 2) (Fig. 2). By observ- Fig. 1. Mean reaction norms for leaf ecophysiological traits (sto- ing all seasons, the mean chlorophyll a/b ratio dif- matal density; specific leaf area; total chlorophyll concentration) of Iris variegata genotypes originating from Shaded habitat () fered between the two years (significant year-effect, and Open habitat (). P<0.0001) (Table 2). Results of repeated ANOVA on the Chla/b dif- shows significant differences in the pattern of SLA ferences of consecutive seasons revealed a statisti- change through seasons between the two years (Table cally significant season-effect (P<0.0001), indicating 1). Individual ANOVAs implemented on each of the a different pattern of change of mean values for the three contrast variables (spring-summer; summer-fall observed trait between seasons. Remaining sources and spring-fall) found significant mean effect for all of differences in within-subject data were also statis- three time-periods, which indicates that there were tically significant. Significant season x year interac- significant differences between all three parts of the tion (P<0.0001) (Table 2) testified that mean values vegetative seasons (Table 1, Fig. 1). of chlorophyll a/b ratio changed in different ways The total chlorophyll concentrations were higher during the two years. Significant season x habitat in- in the shaded than in the open habitats across all sea- teraction (P=0.0038) revealed significant differences sons in both monitored years (significant habitat effect, in seasonal changes of the mean values of Chla/b in P<0.0001) (Fig. 1, Table 1). Unlike the previously ana- genotypes from different habitats (Table 2). The re- lyzed morphological and anatomical traits (SLA and sults of a profile analysis of the within-subject data SD), for total chlorophyll concentration there was not showed that differences in the chlorophyll a/b ratios found a significant year-effect, which led to the conclu- were not the same at all times during the year. There sion that ChlT did not differ between adjacent years was a general tendency for the average chlorophyll a/b (Table 1). Univariate tests for within-subject effects re- ratio to decrease from spring to summer and to main- vealed two significance sources of differences: season tain the reached level from the summer to fall time- (P<0.0001) and season x habitat (P<0.0001) (Table 1). period (Fig. 1). Individual ANOVAs implemented on The season effect showed significant change in mean each of the three contrast variables (spring-summer; values of total chlorophyll concentrations throughout summer-fall and spring-fall) found significant mean the seasons. Also, significant season x habitat interac- effect for two time-periods: the spring-summer and tion indicates the different nature of changes in mean spring-fall, which explains the significant differences 1232 Živković et al.

Table 2. Repeated model analysis of variance (ANOVA) and PROFILE analysis for three Iris variegata leaf traits (chlorophyll a/b ratio; carotenoid concentration; Chla/Carotenoids ratio) in genotypes from contrasting light habitats observed across seasons (spring, summer, fall) in two consecutive years. Source of variation Chlorophyll a/b ratio Carotenoids concentration Chla/Carotenoids ratio Between-subject df MS F MS F MS F Year 1 0.65 47.20**** 213.92 2.96 430.12 13.88*** Habitat 1 0.25 18.46**** 752.51 10.41** 31.18 1.01 error 144 0.01 72.26 30.98 Within-subject Season 2 1.39 133.94**** 253361.64 3456.00**** 514.64 16.63**** Season x Year 2 0.21 20.53**** 230.40 3.14* 347.18 11.22**** Season x Habitat 2 0.05 5.69** 605.01 8.25*** 150.81 4.87** error 288 0.01 30.94 30.94 Profile analysis Spring-Summer 1 4.18 345.02**** 757994.67 3472.16**** 117.48 250.30**** Summer-Fall 1 1.57x10-6 0.00 5.73 10.77** 1898.76 20.24**** Spring-Fall 1 4.18 174.89**** 762169.48 3448.33**** 1071.63 11.73*** *P <0.05; ** P <0.01; *** P <0.001; **** P< 0.0001.

between spring and summer as well as between spring and fall, but not between summer and fall (Table 2).

The mean reaction norms for carotenoid concentration showed that mean values were higher in genotypes from the shaded in comparison with genotypes from the open habitat through all three seasons (Table 2). An identical pattern was registered in both analyzed years (Fig. 2).

The obtained data revealed a statistically significant habitat-effect (P=0.0015) indicating that the mean carotenoid concentrations significantly differed between clones occurring in different habitats while the mean response curve for the second between- subject factor (year) showed no statistical significant outcome (Table 2).

Fig. 2. Mean reaction norms for leaf ecophysiological traits (chlo- The repeated ANOVA analysis on Car uncovered rophyll a/b ratio; carotenoids concentration; chlorophyll a/carotenoids ratio) of Iris variegata genotypes originating from Shaded that all sources of differences in within-subject data habitat () and Open habitat ( ). were statistically significant. Season-effect (P<0.0001) revealed a significant change in the mean values of carotenoid concentrations through different parts of the vegetation periods (Table 2). Season x habitat interaction (P=0.0003) as well as season x year interaction (P=0.0446) were statistically significant. The first interaction indicates that mean values of the Variation of leaf traits of Iris variegata 1233 observed trait change in different ways in genotypes DISCUSSION from different habitats across all seasons. The second Mean daily radiation prevailing in Deliblato Sands interaction uncovers a significantly different pattern inevitably decreases during the course of the year of change in carotenoid concentration in the different due to an increase in vegetation cover – both under years (Table 2). Individual ANOVAs implemented on the forested understory (shaded habitats) and on the each of the three contrast variables (spring-summer; open dune sites (open habitats). It would be reason- summer-fall and spring-fall) found a significant mean able to expect that the stomatal density of successive effect for all three time-periods, which explains why leaves during the vegetative season alters in parallel there were significant differences in the carotenoid with changes in the amount of photosynthetically ac- concentrations in Iris variegata plants between spring tive radiation experienced during development (Tucić and summer, between spring and fall, and between et al., 1999). In this study, it is quite clear that stomatal summer and fall (Table 2). density in I. variegata changed in an expected manner The last analyzed data determining plant physi- in the second analyzed year. The increase in the num- ological response to alternative light regimes were the ber of stomata per leaf area that was found in the fall chlorophyll a/carotenoids ratios. Data showed that season of the first observed year despite a continuous clones from shaded habitat had higher mean values decrease in light intensity could be ascribed to the of this trait in spring and summer in both years. In impacts of other attributes in their environment. The the last vegetation period, fall clones from the open humidity of the external and internal environments of a leaf can be important in influencing its stomatal habitat had higher mean values of chlorophyll a/ca- density and size. The more arid the conditions, the rotenoids ratio compared to clones from the shaded greater number of stomata per leaf area and the steep- habitat in both years. er the insertion gradient in stomatal density between Results from repeated ANOVA suggested sig- successive leaves (Fanourakis, 2013). Since annual nificant year-effect (P<0.0003), which means that changes in air temperature and dryness of the soil in the observed trait mean values differed between the Deliblato Sands can significantly differ over the years (Table 2). Habitat-effect did not demonstrate years, it is possible that the effects of these changes a significant impact on the observed subjects (Table can override the effects of reduced light, resulting in a 2). Results of repeated ANOVA of the differences of higher number of stomata per leaf area than expected. consecutive seasons revealed a statistically significant As well as stomatal density, specific leaf area in I. season-effect (P<0.0001), indicating different mean variegata changed in accordance to the ecophysiologi- values for the observed trait during the three seasons. cal predictions for adaptive phenotypic responses to Other sources of differences in the within-subject light changes (Vandenbussche, 2005; Franklin, 2008). data were also statistically significant (Table 2). Sea- Previously conducted research on the related spe- son x year interaction (P<0.0001) testified that mean cies Iris pumila L. inhabiting the same territory but values of the chlorophyll a/carotenoids ratio changed to some degree different habitats than Iris variegata, in different ways in the two years during the vegeta- showed the advantages of a particular plant model tive seasons. Season x habitat interaction (P=0.0083) system for various genetic, ecological and evolution- revealed a significant change in the mean values in ary studies (Tucić et al., 1998; Avramov et al., 2007; genotypes from different habitats (Table 2). The re- Tarasjev, 2012). It has been previously assessed that sults of a profile analysis of the within-subject data genotypes of the congeneric Iris pumila display a re- have shown that differences in Chla/Car were statisti- markable variability in response to variation in the cally significant at all times during the year, implying light conditions they happen to encounter (Tucić et significant differences between all three parts of the al., 1998; Avramov et al., 2007). Unlike this conge- vegetative seasons. neric species that occurs mostly in sun-exposed sites 1234 Živković et al. and can be classified as a shade-avoiding species, I. centration, which influences their ratio substantially variegata occurs equally in sun-exposed and under- (Ricks and Williams, 1975; Franklin, 2005). Pheno- story sites. These previous data were used to compare typic variation in the physiological traits (Chla/b; the phenotypic responses of the two congeneric Iris ChlT) of Iris variegata in response to different light species. Prevailing radiation levels imply that shade- conditions showed in many ways a similar pattern induced modifications in photosynthetically active of change to those of the mentioned reports on the surface area relative to plant biomass are indeed ben- differential change of photosynthetic pigments under eficial for light inception in Iris pumila (Avramov, the same stress. 2007). In an earlier study, it was reported that under Carotenoid concentrations were higher in geno- reduced light intensity Iris pumila plants exhibited types originating from the shaded compared to those increased leaf expansions, as well as extended leaf from the open habitat. The mode of change is not the longevity relative to plants grown in exposed habi- same in the two years, but the pattern of change in tats (Tucić et al., 1998). The mean values of SLA of carotenoid concentrations between genotypes from Iris variegata were higher in the shaded than in the different habitats was the same during seasons in a open habitat, across all seasons. The decrease in SLA single year (Nikolić, 2005; Kostić, 2012). that was found in the summer period of the first observed year, in spite of a continuous decrease in light Data from previous studies clearly show that in intensity, may be explained by the impacts of other a light-stress environment the chlorophyll a/carot- environmental factors (Schmitt, 2003). enoids ratio will be changed in favor of carotenoids, which serve as photoprotective pigments (Sanchez- During their growth, plants experience different Gomez, 2006). This has to be considered with cau- light conditions that may have an important effect on tion because other biochemical and physiological stomatal characteristics (Al Afas et al., 2007; Poorter mechanisms of photoprotection are commonly found et al., 2009; Loranger and Shipley, 2010). A positive in plants in environments with high irradiance (Gon- relationship between irradiance level and stomatal calves et al., 2001, Franco et al., 2007, Lichtenthaler density is also well documented (Cai, 2004). Results et al., 2007). from this study have shown that the magnitude of the mean phenotypic response changed during the time In this study, results deviating from expectations course. Primarily, the mean values of stomatal densi- occurred in the fall of both years, with particular ties were higher in the open compared to the shaded differences noticeable in the second year. The op- habitats in both analyzed years, which corresponds to posite trend can be explained by the fact that plants already mentioned positive connection between radi- are already adapted to the existing light conditions. ance level and stomatal density. (Capuzzo, 2012). However, change in photosynthetic pigment content is not exclusively an indication of Previous reports showed a quantitative loss in a stressful light environment. For example, contents photosynthetic pigments, differential changes in chlo- of chlorophyll a, chlorophyll b, total chlorophyll and rophyll a/b ratio, remarkable changes in carotenoid carotenoid pigment could also be changed due to the composition in general, and alterations in the com- decrease of soil moisture content (Yan, 2011). position of xanthophyll cycle pigments in particular, in response to stress factors (Vandenbussche, 2005; Since the results obtained from this experiment Biswal, 2011). largely confirmed theoretical expectations concerning adaptation to light changes (with the exception of the Under stressful conditions, concentrations of results for SD obtained in the fall of the first analyzed chlorophyll pigments decline in relation to carotenoid year; results for SLA that significantly differed between concentration. The concentration of chlorophyll b alternative habitats in the same seasons in the two dif- also declines in comparison to chlorophyll a con- ferent years, and results for Chla/Car for the fall of the Variation of leaf traits of Iris variegata 1235 second observed year), we found this species interest- Cao, K. and E.W. Booth (2001). Leaf anatomical structure and ing for further study of the plasticity and variability photosynthetic induction for seedlings of ﬁve dipterocarp species under contrasting light conditions in a Bornean in plasticity of Iris variegata genotypes in response to heath forest. J. Trop. Ecol. 17,163-175. defined and controlled experimental light conditions, Capuzzo, J. P., Rossatto D. R. and A.C. Franco (2012). Differences and to gain insight into potential differences in the se- in morphological and physiological leaf characteristics lection regimes between natural habitats. between Tabebuia aurea and T. impetiginosa is related to their typical habitats of occurrence. Acta Bot. Brasilica. 26(3), 519-526. Acknowledgments: This work was funded by the Minis- Ciolfi, A., Sessa, G., Sassi, M., Possenti, M., Salvucci, S., Carabelli, try of Education, Science and Technological Development M. and G. Morelli (2013). Dynamics of the shade-avoidance of Serbia (project OI 173025 “Evolution in heterogeneous response in Arabidopsis. Plant Physiol. 163 (1), 331-353. environments: mechanisms of adaptation, biomonitoring De Jong, G. (2005). Evolution of phenotypic plasticity: Patterns of plasticity and the emergence of ecotypes, New Phytol. and conservation of biodiversity”). 166, 101-118. Authors’ contributions: Study conception and design Fanourakis, D., Pieruschka, R., Savvides, A., Macnish, A.J., Sar- likioti, V. and E.J. Woltering, (2013). Sources of vase life were done by Stevan Avramov, Aleksej Tarasjev and Uroš variation in cut roses: a review. Postharvest Biol. Technol.78, Živković. Experimental work was performed by Uroš 1-15. Živković. Statistical analysis and interpretation of the result Ferreira, G.A. (2013). Plastic responses in tree architecture and as well as drafting of manuscript were done by all authors. specific leaf area of Xylopia aromatica (Annonaceae): adap- tations to environments with different light intensities. Rev Conflict of interest disclosure: None of the authors of this Bras. Bot. 36, 279-283. manuscript has personal or financial relationship with peo- Franco, A.C., Matsubara, S. and B. Orthen (2007). Photoinhibi- ple or organizations that could influence or bias the work tion, carotenoid composition and the coregulation of pho- and results presented in this paper. tochemical and non-photochemical quenching in neotropi- cal savanna trees. Tree Physiol. 27 (5), 717-725. Franklin, K.A. (2008). Shade avoidance. New Phytol. 179 (4), 930- 944. REFERENCES Franklin, K.A. and G.C. Whitelam (2005). Phytochromes and shade-avoidance responses in plants. Ann. Bot. 96 (2), Al Afas, N., Marron, N. and R. Ceulemans (2007). Variability in 169-175. Populus leaf anatomy and morphology in relation to can- Goncalves, J.F.C., Marenco, R.A. and G. Vieira (2001). Concentra- opy position, biomass production, and varietal taxon. Ann. tion of photosynthetic pigments and chlorophyll fluores- For. Sci. 64, 521-532. cence of mahogany and tonka bean under two light envi- Avramov, S., Pemac, D. and B. Tucić (2007). Phenotypic plasticity ronments. Braz. J. Plant Physiol. 13. 149-157. in response to an irradiance gradient in Iris pumila: adap- Gratani, L. (2014). Plant phenotypic plasticity in response to tive value and evolutionary constraints. Plant Ecology. 190 environmental factors. Advances in Botany, 2014, Article (2), 275-290. ID 208747. Ballare, C.L. (2014). Light regulation of plant defense. Annu. Rev. Halliday, K.J. (1994). Phytochrome B and at least one other phy- Plant Biol. 65, 335-363. tochrome mediate the accelerated flowering response of Biswal B., Joshi, P.N., Raval, M.K. and U.C. Biswal (2011). Photo- Arabidopsis thaliana (L.) to low red/far red ratio. Plant synthesis, a global sensor of environmental stress in green Physiol. 104, 1311-1315. plants: stress signalling and adaptation. Curr. Sci. 101 (1), Hiscox, J. D. and G.F.M. Isrealstom (1979). A method for the 47-56. extraction of chlorophyll from leaf tissue without macera- Bjorkman, O. (1981). Responses to different quantum ﬂux densi- tion. Can. J. Bot. 57, 1332-1334. ties. In: Physiological plant ecology, Encyclopedia of plant Kostić O., Mitrović, M., Knezević M., Jarić S., Gajić G., Đurđević physiology (Eds. O.L. Lange, P.S. Nobel, C.B. Osmond, H. L. and P. Pavlović (2012). The Potential of Four Woody Ziegler), 57-101. Springer-Verlag, Berlin. Species for the Revegetation of Fly Ash Deposits From the Bradshaw, A. D. (1965). Evolutionary significance of phenotypic ‘Nikola Tesla - A’ Thermoelectric Plant (Obrenovac, Ser- plasticity in plants. Advan. Genet. 13, 115-155. bia). Arch. Biol. Sci. 64 (1), 145-158. Cai, Z., Qi, X. and K. Cao (2004). Response of stomatal character- Lichtenthaler, H.K. (1996). Vegetation stress: An introduction to istics and its plasticity to different light intensities in leaves the stress concept in plants. J. Plant Physiol. 148, 4-14. of seven tropical woody seedlings. Ying Yong Sheng Tai Xue Lichtenthaler, H., Sarijeva, G. and M. Knapp (2007). Differences Bao, 15 (2), 201-204. in photosynthetic activity, chlorophyll and carotenoid lev- 1236 Živković et al.

els, and in chlorophyll fluorescence parameters in green Schmitt, J., Stinchcombe, J.R., Heschel, M.S. and H. Huber (2003). sun and shade leaves of Ginkgo and Fagus. J. Plant Physiol. The adaptive evolution of plasticity: Phytochrome-medi- 164, 950-955. ated shade avoidance responses. Integr. Comp. Biol. 43 (3), Loranger, J. and B. Shipley (2010). Interspecific covariation 459-469. between stomatal density and other functional leaf traits Statistical Analysis System Institute, Inc. (2010) The SAS System in a local flora. Botany 88, 30-38. for Windows, release 9.3., Cary (NC): SAS Institute. Mattson, N.S. and J.E. Erwin (2005). The impact of photoperiod Sultan, S.E. (2003). Phenotypic plasticity in plants: A case in eco- and irradiance on flowering of several herbaceous orna- logical development. Evol. Dev. 5, 25-33. mentals. Sci. Hortic. 104 (3), 275-292. Sultan, S.E. and F.A. Bazzaz (1993). Phenotypic plasticity in Poli- Nicotra, A.B., Chazdon, R.L. and C.D. Schlichting (1997). Patterns gonum persicaria I. Diversity and uniformity in genotypic of genotypic variation and phenotypic plasticity of light norms of reaction to light. Evolution 47, 1009-1031. response in two tropical Piper (Piperaceae) species. Am. J. Tarasjev, A. (1997). Flowering phenology in natural populations Bot. 84, 1542-1552. of Iris pumila. Ecography. 20, 48-54. Nikolić, B., Drinić, G., Janjić, V., Šantrić, Lj. and V. Jovanović Tarasjev, A., Barišić- Klisarić, N., Stojković, B. and S. Avramov (2005). Primena metode fluorescencije hlorofila u her- (2009). Phenotypic plasticity and between population dif- bologiji i ispitivanju dejstva herbicida - 1. uticaj različitih faktora na dejstvo herbicida sulfosata. Iugosl. Physiol. Phar- ferentiation Iris pumila transplants between native open and macol. Acta. 14(2), 57-64. anthropogenic shade habitats. Russ. J.Genet. 45, 944-952. Oguchi, R., Hikosaka K. and T. Hirose (2003). Does the photosyn- Tarasjev, A., Avramov, S. and D. Miljković (2012). Evolutionary thetic light-acclimation need change in leaf anatomy? Plant biology studies on the Iris pumila clonal plant: Advantages Cell Environ. 26, 505-512. of a good model system, main findings and directions for Pazourek, J. (1970). The effect of light intensity on stomatal fre- further research. Arch. Biol. Sci. 64, 159-174. quency in leaves of Iris hollandica hort., var. Wedgwood. Tucić, B., Tomić, V., Avramov, S. and D. Pemac (1998). Testing Biol. Plant. 12, 208-215. the adaptive plasticity of Iris pumila leaf traits to natural Pemac, D. and B. Tucić (1998). Reaction norms of juvenile traits light conditions using phenotypic selection analysis. Acta to light intensity in Iris pumila (Iridaceae): A comparison Oecol. 19, 473-481. of populations from exposed and shaded habitats. Plant. Tucić, B., Pemac, D., Stojković , B. and S. Avramov (1999). Coping Syst. Evol. 209, 159-176. with environmental changes in Iris pumila: a pilot experi- Pigliucci, M. (2001). Phenotypic plasticity: Beyond nature and ment. Arch. Biol. Sci. 51, 137-148. nurture, John Hopkins University Press. Valladares, F. and R.W. Pearcy (1998). The functional ecology of Poorter, L. (2001). Light-dependent changes in biomass allocation shoot architecture in sun and shade plants of Heteromeles and their importance for growth of rain forest tree species. arbutifolia M. Roem., a Californian chaparral shrub. Oeco- Funct. Ecol. 15, 113-123. logia 114, 1-10. Poorter, H., Niinemets, U., Poorter, L., Wright, I.J. and R. Villar Valladares, F. and E. Gianoli (2012). Studying phenotypic plastic- (2009). Causes and consequences of variation in leaf mass ity: the advantages of a broad approach. Biol. J. Linn. Soc. per area (LMA): a meta-analysis. New Phytol. 182, 565-588. Lond. 105 (1), 1-7. Ricks, G.R. and R. J. H. Williams (1975). Effects of athmo- Vandenbussche, F., Pierik, R., Millenaar, F.F., Voesenek, L.A. and spheric pollution on deciduous woodland. Part 3: Effects D. VanDerStraeten (2005). Reaching out of the shade. Curr. on photosynthetic pigments of leaves of Quercus petraea Opin. Plant Biol. 8, 462-468. (Matuschka) leibl. Environ. Pollut. 8, 97-106. Ruberti, I., Sessa, G., Ciolfi, A., Possenti, M., Carabelli, M. and G. Wild, A. and G. Wolf (1980). The effect of different light intensi- Morelli (2012). Plant adaptation to dynamically changing ties on the frequency and size of stomata, the size of cells, environment: The shade avoidance response. Biotechnol. the number, size and chlorophyll content of chloroplasts Adv. 30(5), 1047-58. in the mesophyll and the guard cells during the ontogeny Sanchez-Gomez, D., Valladares, F. and M.A. Zavala (2006). Func- of primary leaves of Sinapis alba. Z. Pflanzenphysiol. 97 tional traits and plasticity in response to light in seedlings (4), 325-342. of four Iberian forest tree species. Tree Physiol. 26 (11), Yan, S.Y., Zhou, Z.Y., Zou, L.N. and Y. Qin (2011). Effect of 1425-1433. drought stress on physiological and biochemical proper- Schlichting, C.D. and M. Pigliucci (1998). Phenotypic evolution: A ties of Amorpha fruticosa seedlings. Arid Zone Res. 28 (1), reaction norm perspective, Sinauer Associates Inc. 139-145.