RESEARCH PAPER

Morphological variation of Aechmea distichantha(Bromeliaceae) in a Chaco forest: habitat and size-relatedeffectsL. Cavallero1,3,4, D. Lopez2,5 & I. M. Barberis2,3

1 Facultad de Humanidades y Ciencias, Universidad Nacional del Litoral, Argentina

2 Facultad de Ciencias Agrarias, Universidad Nacional de Rosario, Zavalla, Argentina

3 Consejo Nacional de Investigaciones Cientıficas y Tecnicas (CONICET), Argentina

4 Present address: Laboratorio Ecotono, Centro Regional Universitario Bariloche, Universidad Nacional del Comahue,

San Carlos de Bariloche, Rıo Negro, Argentina

5 Present address: INTA Bariloche. CC 277, Bariloche, Rıo Negro, Argentina

INTRODUCTION

During their life cycle, plant species may exhibit differ-ent types of variation. Phenotypic traits may vary as afunction of the environment, ontogeny or both(McConnaughay & Coleman 1999; Wright & McConn-aughay 2002; Weiner 2004). The first type of variationcould be associated with adaptive phenotypic plasticity(‘true’ phenotypic plasticity), which is the potential ofan organism to produce a range of different, relativelyfit phenotypes in response to different environmentalconditions (DeWitt et al. 1998). This subject has been ofgreat interest to ecologists and evolutionary biologistsfor many years, because of the importance of heteroge-neous environments in the ecology and evolution of spe-cies (Schlichting 1986; Schlichting & Pigliucci 1998; de

Kroon et al. 2005; Pigliucci 2005; Miner et al. 2005). Inrecent years, a plethora of phenotypic plasticity studieshave emerged focusing on plant ecological development(i.e. a genuinely integrated view of plant development inthe real environmental context; see Ackerly et al. 2000;Sultan 2004; Chambel et al. 2005; Sultan & Soltis 2005;Ackerly & Sultan 2006; Bradshaw 2006; Magyar et al.2007; Valladares et al. 2007). True phenotypic plasticityin plants is usually explained by the Optimal Partition-ing Theory, which states that plants respond to varia-tions in the environment by allocating biomass amongseveral plant organs to optimise the capture of light,water, nutrients and carbon dioxide and thus maximiseplant growth rate (Bloom et al. 1985). The response ofplant species to light quantity or quality has been oneof the most widely studied factors affecting phenotypic

Keywords

Bromeliads; phenotypic plasticity; plant

architecture; size-related variation;

understorey.

Correspondence

L. Cavallero, Facultad de Humanidades y

Ciencias, Universidad Nacional del Comahue,

San Carlos de Bariloche, Rıo Negro,

Argentina.

E-mail: lcavallero@crub.uncoma.edu.ar

Editor

J. Knops

Received: 15 January 2008; Accepted: 1 June

2008

doi:10.1111/j.1438-8677.2008.00123.x

ABSTRACT

Plants show different morphologies when growing in different habitats, butthey also vary in their morphology with plant size. We examined differencesin sun- and shade-grown plants of the bromeliad Aechmea distichantha withrespect to relationships between plant size and variables related to plantarchitecture, biomass allocation and tank water dynamics. We selected vege-tative plants from the understorey and from forest edges of a Chaco forest,encompassing the whole size range of this bromeliad. Plant biomass waspositively correlated with most architectural variables and negatively corre-lated with most biomass allocation variables. Understorey plants were tallerand had larger diameters, whereas sun plants had more leaves, larger sheatharea, sheath biomass and sheath mass fraction. All tank water-related vari-ables were positively correlated with plant biomass. Understorey plants hada greater projected leaf area, whereas sun plants had higher water contentand evaporative area. Plasticity indices were higher for water-related thanfor allocation variables. In conclusion, there were architectural and biomassallocation differences between sun- and shade-grown plants along a size gra-dient, which, in turn, affected tank water-related variables.

Plant Biology ISSN 1435-8603

Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands 379

plasticity (Hutchings & de Kroon 1994; Rozendaal et al.2006).

According to the second type of variation, duringgrowth and development, plants experience morphologi-cal, anatomical and physiological changes related to theirpassage through different ontogenetic phases, such as veg-etative growth, flowering and fruiting (Zotz 2000;Schmidt et al. 2001; Zotz et al. 2001; Hietz & Wanek2003). As many allocation patterns follow allometric tra-jectories, some of the plasticity in allocation may simplybe the result of size, or ‘apparent plasticity’ (McConnaug-hay & Coleman 1999; Wright & McConnaughay 2002;Weiner 2004; Chambel et al. 2005). Evans (1972) sug-gested that environmentally induced variation in traits(i.e. ‘true plasticity’) could best be distinguished fromapparent plasticity by comparing plants of the same sizein different habitats.

Both types of variation (i.e. true phenotypic plasticityand size variation or apparent plasticity) have been inde-pendently studied in bromeliad species (Benzing 2000).Phenotypic plasticity to light quantity or quality has beenshown for terrestrial, epiphytic and facultative epiphytes(Cogliatti-Carvalho et al. 1998; Scarano et al. 2002; Freitaset al. 2003), whereas size variations have mainly beenanalysed in epiphytic bromeliad species (Schmidt & Zotz2001; Zotz et al. 2002, 2004; Hietz & Wanek 2003). Intank-forming bromeliads in particular, changes in archi-tecture as plants grow also affect several tank parameters,such as maximum tank water content, water surface inthe tank, evaporation rate, transpiration rate and pro-jected surface area (Zotz & Thomas 1999).

To our knowledge, there is no study that jointly analy-ses habitat and size-related effects on bromeliad morphol-ogy and as a consequence of their tanks. In this study, weexplore variations in plant architecture, biomass alloca-tion and tank water-related variables on a tank bromeliad(Aechmea distichantha Lem.) along a size gradient of indi-viduals growing in shade or sun conditions (i.e. understo-rey or forest edges, respectively). This bromeliad formsdense colonies in the understorey of Schinopsis balansaeEngl. forests (‘quebrachal’, Anacardiaceae) of the South-ern Chaco (Lewis et al. 1997; Barberis & Lewis 2005). Inthese open forests, woody species distribution is relatedto local environmental heterogeneity (Barberis et al.2002). There are patches of closed forest (about 10–12 mtall) in convex areas, which typically alternate withstretches of savanna-type vegetation in plain areas rangingfrom tens to hundreds of meters in width (Barberis et al.2002). The edges between forest patches and savanna-typepatches are more related to microrelief than to distur-bances, as in other Chaco forests (Lopez de Casenaveet al. 1995). Aechmea distichantha is frequently found onthe soil in the understorey and forest edges, but may alsooccur as an epiphyte. It reproduces mainly vegetatively,and ramets from one genet exposed to different environ-mental conditions show different phenotypes (i.e. modu-lar plasticity sensu; de Kroon et al. 2005). Thus, there is amorphological gradient between modules completely

exposed to sun or shade conditions with a full set ofintermediate phenotypes along this light gradient (Caval-lero 2005).

In order to distinguish true phenotypic plasticity fromapparent plasticity (size effects) in plant architecture, bio-mass allocation and tank water-related variables of A. dis-tichantha, we used covariance analyses and multivariatepermutation analyses that included biomass as a covari-ate. If bromeliad morphology is only the result of anadaptation to local environmental conditions, then weexpect differences in plant architecture, biomass allocationand water-related variables for plants growing in differenthabitats (i.e. understorey and forest edges), but no differ-ences due to size (Fig. 1, scenario 1). On the other hand,if bromeliad morphology varies only as a result of plantgrowth, then we expect differences in plant architecture,biomass allocation and water-related variables for plantsalong a size gradient, but no differences between habitats(Fig. 1, scenario 2). Finally, if bromeliad morphology isthe result of an adaptation to local environmental condi-tions and also varies as a result of plant growth, then weexpect that differences in plant architecture, biomass allo-cation and water-related variables for plants growing indifferent habitats will either hold constant (no interactionbetween habitat and size; Fig. 1, scenario 3a) or vary(significant interaction; Fig. 1, scenario 3b) along a sizegradient. In addition, we analysed whether these differ-ent types of variables (i.e. architecture, allocation andwater-related) vary in their response to habitat (i.e. intheir plasticity indices; see Valladares et al. 2000, 2005;Rozendaal et al. 2006).

Fig. 1. Possible scenarios showing the variation of a trait in two con-

trasting habitats along a size gradient. The differences are reflected in

the general linear model: (1) size effect (slope) is not different from

zero, but habitat intercepts are different; (2) slope is different from

zero, but a single slope and intercept fit in both habitats; (3a) slope is

different from zero, and habitat (intercepts) differs; (3b) slope is differ-

ent from zero and different between habitats, and intercepts are dif-

ferent between habitats.

Habitat and size-related effects on bromeliad morphology Cavallero, Lopez & Barberis

380 Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands

MATERIALS AND METHODS

Study area and analysed species

The study was carried out in a 400-ha stand of the S. bal-ansae Engl. forest type located at Las Gamas, Santa Fe,Argentina (29�28¢S, 60�28¢W, 58 m above sea level). Theclimate is humid temperate to warm, with a mean annualtemperature of about 20 �C, and mean annual precipita-tion of about 1000 mm. Rainfall is concentrated in sum-mer (December–March) and a dry season of variablelength occurs in winter (June–August). The forest islocated on a mosaic of soils with low hydraulic conduc-tivity and high sodium content, and the soil surface has anoticeable microrelief (Barberis et al. 1998). In these for-ests, most woody species are deciduous, with small leavesthat frequently have spiny structures (Lewis et al. 1997).

Aechmea distichantha occurs as a terrestrial or epiphyticplant in deciduous, semideciduous and evergreen forestsfrom sea level to an altitude of 2400 m in southern Brazil,Bolivia, Paraguay, Uruguay and northern Argentina(Smith & Downs 1979). It is a tank-forming bromeliad(Ecophysiological Type III sensu Benzing 2000), withleaves arranged in a very dense rosette. Blades are pun-gent with armed borders and the sheaths have entire bor-ders (Smith & Downs 1979).

Habitat description

In the summer (January 2005), we recorded air tempera-ture (�C), relative humidity (%), and maximum windspeed (kmÆh)1) at 10 sites. Measurements were made witha high precision pocket weather station (GEOS 9, Sky-watch, Switzerland) from 1100 h to 1500 h. In each site,we distinguished two habitats (understorey and forestedge) and randomly selected which habitat would bemeasured first. We spent 30 min in each habitat to allowmeasurement stabilisation.

In January 2006, we measured evapotranspiration(mmÆh)1) in the understorey and forest edges of two sitesusing a Model A Etgage (Etgage Co., USA). We alsorecorded photosynthetically active radiation (PAR) at foursites using integrating light quantum sensors (LI-191SA;LI-COR Inc., USA). In each site, PAR measurements wererecorded simultaneously from one sensor located in eachhabitat and connected to a data logger (1000 Data Log-ger; LI-COR Inc.). Within each habitat, we randomlyselected six locations, where we took three instantaneousPAR measurements. Finally, we also measured volumetricsoil moisture content in the understorey and forest edgesof five sites. In each habitat, we randomly selected fivelocations and took three samples using the ThetaKit v3(Delta T Devices, UK).

Sampling procedure

In June 2004, we selected 27 plants in the vegetativephenological state from the understorey and 28 plantsfrom forest edges. The ramets used were at least 5 m

from each other in order to assure genet independence.The plants encompassed the full size range of A. disti-chantha in our study area. In the field, we measuredthe height from the soil to the top leaf for each plant,the largest diameter and its transversal. In order to esti-mate actual water content, plants were carefully dis-lodged from the soil, and the water contained insidethe tanks was poured into buckets and measured withgraduated cylinders.

Plants were taken to the lab and photographed fromabove with a digital camera (Sony P-52; USA) (Zotz &Thomas 1999). We put a rectangle of a known areabeside each plant and subsequently calculated the pro-jected area of each plant using Auto Cad 2004 (AutodeskInc., USA). Each plant was washed to remove all debrisfound inside the leaf bases. Plants were then placed insidea bucket and a known amount of water (ml) was pouredinto the tank until the tank capacity was filled. The maxi-mum tank water content was estimated as the differencebetween the known added volume and the water draininginto the bucket. The maximum water surface of a tank(i.e. maximum evaporative area) was obtained by fillingthe tank of each plant with melted paraffin (Zotz & Tho-mas 1999). After paraffin solidification, leaves were care-fully removed in order to obtain a block of solid paraffinfrom each sheath. The contour of the upper area of eachparaffin block was drawn on paper, and the evaporativearea was obtained by the gravimetric method (Freitaset al. 2003). The evaporative area of the whole tank wasobtained by summing all evaporative areas. The followingvariables were derived from the data: water content perleaf = maximum water content ⁄ number of evaporativeareas (ml leaf )1); evaporative area per leaf = evaporativearea of the whole tank ⁄ number of evaporative areas (cm2

leaf )1); and the water content per evaporative arearatio = maximum water content ⁄ evaporative area of thewhole tank (mlÆcm)2).

For each plant, we counted the leaf number and sepa-rated each leaf into its blade and sheath. Each blade andsheath was pressed and outlined on paper, and then thepaper outlines were cut and weighed (SCALTEC SBA 32,d = 0.0001 g, Germany) to estimate blade and sheath areasusing the gravimetric method (Freitas et al. 2003). Plantblades, sheaths and stems were oven-dried at 70 �C to con-stant weight (SCALTEC SBA 52, d = 0.01 g, Germany).

Finally, we derived the following biomass allocationvariables from the data: blade area index (BAI) = bladearea ⁄ projected area (cm2Æcm)2); blade area ratio (BAR) =-blade area ⁄ total dry biomass (cm2Æg)1); specific blade area(SBA) = blade area ⁄ blade dry biomass (cm2Æg)1); specificsheath area (SShA) = sheath area ⁄ sheath dry biomass(cm2Æg)1); blade mass fraction (BMF) = blade dry bio-mass ⁄ total dry biomass (gÆg)1); sheath mass fraction(ShMF) = sheath dry biomass ⁄ total dry biomass (gÆg)1);stem mass fraction (SMF) = stem dry biomass ⁄ total drybiomass (gÆg)1); and blade sheath ratio = blade bio-mass ⁄ sheath biomass (gÆg)1). It should be noted that wefocused on plant aboveground allocation.

Cavallero, Lopez & Barberis Habitat and size-related effects on bromeliad morphology

Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands 381

Data analyses

We used the Wilcoxon signed-rank test to analyse whetherthere were differences in temperature, relative humidity,wind speed, evapotranspiration, light intensity and soilwater content between the understorey and forest edges.For light intensity and soil water content, we first averagedthe three recorded values per station, and then used theseaverages to estimate the mean value for each site.

Differences in plant architecture, biomass allocationand tank water-related variables between habitats wereanalysed with general linear models. Habitat was used asa categorical factor and plant biomass as a covariate. Datawere analysed for residual normality and homoscedasticity(Quinn & Keough 2002). Most variables were log10-trans-formed to improve normality and homoscedasticity. SMF,BMF and ShMF were arcsine-square root-transformed,and leaf number and number of evaporative areas werenot transformed. For actual water content, we added 1 toeach value before log10 transformation because severalvalues were zero. The slopes of the relationships betweenthe transformed response variables and logBiomass werecompared using a model that included the logBio-mass · transformed response term. Where the interactionterm was not significant, the model was refitted, assuminga common slope, and intercepts were compared. Interac-tions between habitat and covariate were detected for BAIand the blade ⁄ sheath ratio. Tests were done with 57 indi-viduals for those variables measured in the field and with42 individuals for those variables that needed furtheranalysis (e.g. evaporative area, blade and sheath areas andrelated variables). All analyses were done using the sas

8.0 package (SAS Institute Inc., 1999). We consideredType III Sum of Squares and re-adjusted the P-values forstatistical acceptance with the Hochberg correction(Legendre & Legendre 1998).

We realised that the covariate was measured with errorand thus the use of a Model I regression to analyse thedata may lead either to positive or negative bias or to aninflated Type I error rate (McCoy et al. 2006). However,McCoy et al. (2006) pointed out in their supplementarymaterial that when the range in the covariate is the samefor both groups (as in our data), there do not seem to beeffects of error in the covariate. Moreover, as a correlatefor plant size, we used biomass, which may involve lesserror than using linear traits (McCoy et al. 2006, Suppl.).

We used a permutational multivariate analysis of vari-ance for testing whether there were differences in the setsof architectural, allocation and water-related variablesbetween sun- and shade-grown plants. We included the42 individuals in which we had measured all 23 variables.Data were transformed as in the general linear models,and log total biomass was used as a covariate. Tests weredone with the permanova program (Anderson 2001)based on a correlation matrix and using the Euclideandistance. We further explored differences between plantsfrom the two habitats using the computer program CAP(Canonical Analysis of Principal coordinates; Anderson &

Willis 2003). This generalised discriminant analysis findsthe axes in the principal coordinate space that are best atdiscriminating among a priori groups. Then, the programprovides a misclassification error of individuals to groups(i.e. plants to habitat in our study).

We calculated a plasticity index for each variable toestimate its response to habitat. For most variables, weused the estimated regression equations to obtain theaverage values in each light environment (i.e. habitat).For BAI and blade ⁄ sheath ratio, we did not estimate theaverage value because there were significant interactionsbetween habitat and the covariate. For the other variables,we calculated the phenotypic plasticity index as the differ-ence between the maximum and minimum mean valuesbetween the two light environments in the field dividedby the maximum mean value (Valladares et al. 2005).This phenotypic plasticity index, which ranges from 0 to1, has the advantage that it can be used to comparechanges in variables expressed in different units and withcontrasting variation ranges (Valladares et al. 2005, 2006).We used an anova and Tukey’s pairwise comparison toanalyse whether there were differences in the phenotypicplasticity index among the different types of variable anal-ysed (i.e. architectural, biomass allocation or tank water-related variables). The plasticity indices were square-roottransformed in order to reduced heteroscedasticity(Quinn & Keough 2002).

RESULTS

Habitat description

In the understorey, air temperature, maximum windspeed, evapotranspiration and light intensity were signifi-cantly lower than in forest edges (Table 1). In contrast,no significant differences in relative humidity and soilwater content were detected between habitats (Table 1).

Morphological variation of individuals growing in sunor shade

Most variables related to plant architecture and biomassallocation were significantly correlated with plant bio-mass, whereas six out of the 15 variables were signi-ficantly affected by habitat (Table 2). All architecturalvariables and one allocation variable (ShMF) were posi-tively correlated with plant biomass (Figs 2 and 3),whereas most biomass allocation variables (i.e. BAR, SBA,SShA, BMF, SMF and blade to sheath ratio) were nega-tively correlated with plant biomass (Fig. 3). With regardto habitat, plants growing in the understorey were tallerand had larger diameters (Figs 2 and 3). In contrast,plants growing in the sun had a larger sheath area, sheathbiomass, more leaves and larger ShMF (Figs 2 and 3). ForBAI and blade to sheath biomass ratio, no trend could bedetected because the slopes were not homogeneous(Fig. 3). Finally, there were no significant differences inblade area, blade biomass, BAR, SBA, SShA, BMF and

Habitat and size-related effects on bromeliad morphology Cavallero, Lopez & Barberis

382 Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands

SMF between sun- and shade-grown plants (Fig. 3). Forinformation on slopes, intercepts, standard errors andhabitat · size interactions, see Appendix 1.

All tank water-related variables were positively corre-lated with plant biomass, whereas significant habitateffects were observed in five out of eight variables(Table 2, Fig. 4). Plants growing in the understorey had alarger projected leaf area, whereas plants growing in the

forest edges had higher maximum tank water content,actual tank water content, evaporative area and numberof evaporative areas (Fig. 4). There were no significantdifferences between shade- and sun-grown plants withregard to ratios of tank water content ⁄ leaf, evaporativearea ⁄ leaf and water content ⁄ evaporative area (Fig. 4). Forinformation on slopes, intercepts, standard errors andhabitat · size interactions see Appendix 1.

Table 1. Median and range values for environmental variables recorded in the understorey and forest edges of a Schinopsis balansae forest.

variable (units) Na

understorey forest edges

Pmedian range median range

air temperature (�C) 10 37 (36.0–38.0) 39 (38.0–40.5) *

maximum wind speed (kmÆh)1) 10 1.65 (0.0–3.6) 6.65 (5.1–9.5) *

relative humidity (%) 10 45.0 (44.0–45.5) 43.5 (43.5–44.5)

volumetric soil moisture (%) 5 8.6 (8.0–11.8) 6.7 (5.7–9.8)

evapotranspiration (mmÆday)1) 6 3.5 (2–6) 8.0 (4–9) *

light intensity (lmolÆm)2Æs)1) 4 30 (24–50) 1871 (1773–2056) *

a N = number of sites where the variables were recorded.

*P < 0.05 for the Wilcoxon signed-rank tests.

Table 2. ANCOVA results for variables related to plant architecture, biomass allocation and tank water-related variables.

type of variablea variablesb (units)

biomass habitat

dfc F Pd dfc F Pd

Ar height (cm) 1.54 320.09 <0.0001 1.54 69.80 <0.0001

Ar diameter (cm) 1.54 122.35 <0.0001 1.54 27.90 <0.0001

Ar blade area (cm2) 1.39 682.89 <0.0001 1.39 5.69 0.0220

Ar sheath area (cm2) 1.39 1199.76 <0.0001 1.39 26.24 <0.0001

Ar blade biomass (g) 1.54 2951.78 <0.0001 1.54 4.79 0.0329

Ar sheath biomass (g) 1.54 2160.23 <0.0001 1.54 18.72 <0.0001

Ar leaf number 1.54 75.56 <0.0001 1.54 13.11 0.0006

Al BAI (cm2Æcm)2) 1.39 4.99 0.0313* 1.39 0.67 0.4187*

Al BAR (cm2Æg)1) 1.39 34.14 <0.0001 1.39 5.69 0.0220

Al SBA (cm2Æg)1) 1.39 36.66 <0.0001 1.39 3.82 0.0579

Al SShA (cm2Æg)1) 1.39 57.60 <0.0001 1.39 2.72 0.1073

Al BMF (gÆg)1) 1.54 9.44 0.0033 1.54 6.48 0.0138

Al ShMF (gÆg)1) 1.54 42.16 <0.0001 1.54 20.10 <0.0001

Al SMF (gÆg)1) 1.54 4.97 0.0300 1.54 2.45 0.1231

Al blade sheath ratio (gÆg)1) 1.54 28.73 <0.0001* 1.54 6.14 0.0163*

W projected area (cm2) 1.54 600.04 <0.0001 1.54 16.71 0.0001

W maximum tank water content (ml) 1.54 475.11 <0.0001 1.54 39.78 <0.0001

W water content by leaf (mlÆleaf)1) 1.39 88.88 <0.0001 1.39 6.44 0.0153

W actual tank water content (ml) 1.54 44.22 <0.0001 1.54 25.17 <0.0001

W maximum evaporative area (cm2) 1.39 277.68 <0.0001 1.39 20.48 <0.0001

W number of evaporative areas 1.39 30.99 <0.0001 1.39 10.27 0.0027

W evaporative area by leaf (cm2Æleaf)1) 1.39 122.31 <0.0001 1.39 9.02 0.0046

W water tank evaporative area ratio (mlÆcm)2) 1.39 18.05 <0.0001 1.39 1.26 0.2680

a Type of variable: (Ar) architecture, (Al) allocation, (W) water-related.b Variable codes: BAI = blade area index; BAR = blade area ratio; SBA = specific blade area; SShA = specific sheath area; BMF = blade mass frac-

tion; ShMF = sheath mass fraction; SMF = stem mass fraction.c df = numerator, denominator degrees of freedom.d Bold fonts denote significant results after re-adjusting the P-values with the Hochberg correction (P = 0.0036).

*Significant interaction between biomass and habitat.

Cavallero, Lopez & Barberis Habitat and size-related effects on bromeliad morphology

Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands 383

For all the analysed datasets, the permanova testsshowed significant differences between habitats whenusing bromeliad biomass as a covariate (Table 3). How-ever, differences in architecture and water-related vari-ables were larger than differences in allocation variables(Table 3). According to the CAP analyses, the misclassifi-cation error was lower for architecture and allocationvariables than for water-related variables (Fig. 5; Table 3).

The plasticity indices varied according to the type ofvariable (F2,18 = 7.06; P = 0.005). Allocation variables hadlower plasticity indices than tank water-related variables(P < 0.05), whereas architectural variables were not sig-nificantly different from either allocation or water-relatedvariables (Fig. 6).

DISCUSSION

Integrating true and apparent phenotypic plasticity

In our study, almost all of the analysed variables showeda combination of both true and apparent plasticity, andtherefore matched the proposed scenarios 3a and 3b. The

exception was SMF, which showed no trend at all, eitherwith habitat or size. On the one hand, most variables (allvariables related to plant architecture and tank water rela-tions, as well as some allocation variables) matched sce-nario 3a. Therefore, differences in plant morphologybetween A. distichantha individuals grown in the under-storey and in forest edges remained constant along thesize range. On the other hand, BAI and blade sheathratio, which showed a habitat · size interaction, matchedscenario 3b. Hence, differences in plant morphologybetween habitats changed along a size gradient for thesevariables. It is likely that the increased differences in sometraits between plants as they grow towards adulthood indifferent environmental conditions would provide agreater adaptation to the habitat where they are growing,and thus may indicate true adaptive phenotypic plasticity.

True phenotypic plasticity: morphological differencesbetween sun and shade individuals

True phenotypic plasticity might be explained by theOptimal Allocation Theory, which states that plants

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relation to biomass for plants of Aechmea

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conditions in a Schinopsis balansae forest.

Each circle represents a plant. Regression lines

for each group of plants are shown.

Habitat and size-related effects on bromeliad morphology Cavallero, Lopez & Barberis

384 Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands

respond to limiting environmental factors by modifyingresource allocation to multiple organs (Bloom et al.1985). A higher allocation to blades in A. distichanthaplants growing in the understorey could be a competitiveadvantage by allocating more resources to a larger photo-synthethic area that may allow increased light capture inthe low-light environment of the understorey. Moreover,the loose array of leaves reduced leaf overlap and self-shading (Scarano et al. 2002), maximising the photosyn-thetically active area. In contrast, the morphology ofplants growing in forest edges reduced exposure to light.The higher number of leaves would produce larger leafoverlap, reducing the increased light intensity that couldnegatively affect chlorophyll, thus structurally avoidinghigh light stress (Freitas et al. 2003). In addition, lightstress in sun plants is likely to be further reduced becausethe sun plants have more erect leaves than shade plants(Cavallero 2005).

Differences in architectural and biomass allocation vari-ables between shade and sun plants also affected their

ability to capture, retain or lose water from their tanks.Shade plants have a larger projected leaf area, so theymay be able to capture not only more light but also morewater than sun plants. In contrast, sun plants have ahigher tank water-holding capacity (i.e. maximum tankwater content and actual tank water content) than shadeplants. A similar pattern was suggested for Aechmea bro-meliifolia (Rudge) Baker in restingas (i.e. a mosaic ofplant communties on sandy coastal plains) of southernBrazil (Scarano et al. 2002). Maximum evaporative area ishigher in sun plants than in shade plants, which may berelated not only to a slightly higher evaporative area perleaf but also to a higher number of evaporative areas,because sun-grown plants have more leaves than shade-grown plants. However, as sun plants hold more water intheir tanks, there were no significant differences betweensun and shade plants in the water content ⁄ evaporativearea ratio. Sun plants probably experience higherevaporation rates because they are exposed to significantlyhigher irradiance, temperature and wind speed (Table 1).

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log 1

0 B

lade

:She

ath

ratio

(g·

g–1 )

0 1 2 3Arc

sine

-sqr

t ShM

F (g

·g–1

)lo

g 10

SShA

(cm

2 ·g–

1 )

log10 Biomass (g) log10 Biomass (g)

Fig. 3. Variation in biomass allocation

variables in relation to biomass for plants of

Aechmea distichantha growing in forest

edges (empty circles) and understorey (filled

circles) conditions in a Schinopsis balansae

forest. Each circle represents a plant.

Regression lines for each group of plants are

shown.

Cavallero, Lopez & Barberis Habitat and size-related effects on bromeliad morphology

Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands 385

However, for plants of similar size, tank water depletionwould probably occur sooner in shade plants due to thelower tank water content recorded in this study, as wellas on all four different sampling dates in a related experi-ment (Montero, Feruglio, Barberis unpublished data).Moreover, we found several small shade plants that heldalmost no water in their tanks, whereas no sun plantwithout water was recorded. This pattern contradicts theobservations of Lopez & Rios (2001), who examined arestinga in Brazil and found that only shaded bromeliadsretained some water in their tanks, whereas sun plantswere completely dry for at least 1 week. Thus, more stud-ies are needed in order to determine whether there aredifferences between species in the way plasticity affectstank water-related variables.

While true phenotypic plasticity was observed for sev-eral traits in A. distichantha, we are not sure whether this

phenotypic plasticity is adaptive. This is especially impor-tant for clonal plants because, even though clonal life his-tory traits are likely to be adaptive, it is not clear whetherthey are true adaptations (Fischer & van Kleunen 2002).Adaptive plasticity requires heritable genetic variationwith trait effects on fitness, but may be prevented by con-straints, costs and trade-offs (DeWitt et al. 1998; Alpert &Simms 2002; Fischer & van Kleunen 2002; van Kleunen &Fischer 2005). Moreover, plants are generally exposed tomultifactor environments and to simultaneous interac-tions with many other species, thus phenotypic plasticitytakes place within an ecological context (Valladares et al.2007). We also realise that our study has several caveats.First, our findings were based on a descriptive study andwe did not manipulate the light environment or the allo-cation of individuals to each light treatment (Valladareset al. 2006). In addition, we did not measure plant traits

Fig. 4. Variation in water relations variables

in relation to biomass for plants of Aechmea

distichantha growing in forest edges (empty

circles) and understorey (filled circles)

conditions in a Schinopsis balansae forest.

Each circle represents a plant. Regression lines

for each group of plants are shown.

Habitat and size-related effects on bromeliad morphology Cavallero, Lopez & Barberis

386 Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands

along a growth-development path in each environmentand thus we were not able to determine when plasticityoccurred (Chambel et al. 2005). Second, we did not usemanipulated genotypes, phenotypes or clones of the sameindividual (Ackerly et al. 2000; Valladares et al. 2006).Therefore, comparative studies with sympatric species are

needed in order to evaluate adaptive phenotypic plasticityin bromeliads and such studies should take into accountthe suggestions of Valladares et al. (2006).

Apparent phenotypic plasticity: morphological differencesrelated to individual size

Our study showed apparent phenotypic plasticity forA. distichantha plants. Most architectural and tank water-related variables and one biomass allocation variable(ShMF) increased as the size of the individual increased.In contrast, all other biomass allocation variables werereduced as the size of the individual increased. Morpho-logical and physiological changes with plant size havebeen recorded for several epiphytes, and these size-relatedvariations are usually associated with changes in thearea ⁄ volume ratio. The latter could be related to changesin transpiring area ⁄ tissue water content or changes in leafarea ⁄ tank water content. These changes, in turn, couldhave profound effects on growth and survival of theseepiphytes (Schmidt et al. 2001; Zotz et al. 2001).

Even though smaller plants of A. distichantha may bemore dependent on rainfall than larger ones, as observedfor other epiphytic bromeliads (Zotz & Thomas 1999), itshould be noted that most A. distichantha individuals, likeother Aechmea species that grow in the understorey(Villegas 2001; Sampaio et al. 2005), mainly reproducevegetatively. Thus, many small individuals may survivedry periods due to water and nutrient supply from theirmother plant because of module integration (de Kroonet al. 2005). Unfortunately, detailed analyses on moduleintegration in bromeliads are lacking, and hence thismechanism requires more study.

Habitat heterogeneity and phenotypic plasticity

It has been suggested that habitat heterogeneity favoursthe evolution of plastic genotypes (Alpert & Simms 2002,van Kleunen and Fischer 2005). Plastic responses areselected when environments are spatially and temporallyheterogeneous at a scale relevant to the plant (vanKleunen & Fischer 2005; Magyar et al. 2007). In clonalplants, like A. distichantha, the latter is especially

Table 3. Results of multivariate tests for different sets of variables related to plant architecture, biomass allocation and tank water-related vari-

ables.

set of variables

biomass habitat CAP

dfa F P dfa F P Eigenvalue MEb

architecture 1.39 81.65 0.0002 1.39 5.33 0.0030 0.801 9.52

allocation 1.39 13.36 0.0002 1.39 3.31 0.0156 0.823 11.10

tank water-related 1.39 63.69 0.0002 1.39 6.94 0.0010 0.769 16.67

For the PERMANOVA tests, the effects of biomass and habitat are shown.

For the Canonical Analysis of Principal coordinates analyses, the eigenvalues and the misclassification errors are presented.a df = numerator, denominator degrees of freedom.b ME = misclassification error (%).

Fig. 5. Dispersion of individuals of Aechmea distichantha along the

first axis of the Canonical Analysis of Principal coordinates (CAP) for

different sets of variables (architecture, allocation and water-related

variables). Empty circles represent sun-grown individuals and filled cir-

cles are shade-grown plants.

Fig. 6. Plasticity index of the architectural, biomass allocation and

water-related variables for large and small plants grown in sun and

shade habitats. Error bars indicate ± SE. Different letters above bars

indicate significant differences between types of variables (P < 0.05).

Cavallero, Lopez & Barberis Habitat and size-related effects on bromeliad morphology

Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands 387

important because different rosettes may experience dif-ferent environmental conditions.

The observed phenotypic plasticity in A. distichanthawas probably favoured by the highly heterogeneous habi-tats of the S. balansae woodlands (Barberis et al. 2002;Barberis & Lewis 2005). In our forest, individuals of thestudy species are mainly found in the understorey (Barbe-ris et al. 1998; Barberis & Lewis 2005), whereas smallpatches of sun-grown plants are scattered along forestedges. This pattern is similar to the spatial distribution ofA. bromeliifolia populations in different habitats in restin-gas from southern Brazil (Scarano et al. 2002). Theseauthors showed, for A. bromeliifolia, that populationsgrowing in flooded or shaded conditions were acclimated,whereas populations from exposed, unflooded habitatsseemed to be under stress. Likewise, our results suggest asimilar pattern for A. distichantha, where the shade mor-photype may be acclimated to understorey environmentsand the forest-edge morphotype may be acclimated tothese environments, whereas individuals exposed to fullsun seem to be under stress (i.e. higher irradiance andexcess water loss by evapotranspiration). Nevertheless,ecophysiological studies are needed in order to elucidatewhether or not the plants are under stress.

CONCLUSIONS

There are morphological differences in architecture andbiomass allocation between sun- and shade-grown plantsof A. distichantha, which are observed along a plant sizegradient. Habitat and size-related morphological differ-ences affect tank water capture, accumulation and loss,which in turn may affect direct and indirect interactions.The presence of plastic species able to colonise the differ-ent environments of heterogeneous ecosystems, such asA. distichantha, could play an important role in commu-nity structuring and recovery in ecosystems that areanthropically altered by overgrazing, logging and climatechange.

ACKNOWLEDGEMENTS

We thank R. Commuzzi, L. Schaumburg and S. Acostafor their help in Las Gamas. This work is part of L. Cav-allero’s thesis for the Licenciate in Biodiversity degree.Funding was provided by FONCYT (BID-1201 ⁄ OC-AR-PICT 01-12686) and The Rufford Maurice Laing Founda-tion. IMB acknowledges a postdoctoral fellowship fromCONICET. G. Montero and L. Galetti helped to collectthe environmental data. D. Tuesca, J.L. Vesprini, M. Past-orino and two other reviewers helped to improve themanuscript.

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Appendix 1. Regressions of architecture, allocation and water-related variables with size (total biomass) for plants of Aechmea disti-

chantha growing in the understorey or at forest edges.

variable habitat

biomass

estimate

biomass

error

intercept

estimate

intercept

error R2 df F P-value

Habitat

· biomass

height shade 0.337 0.0270 1.268 0.0492 0.857 1.26 156.23 <0.0001 0.9939

sun 0.337 0.0269 1.104 0.0512 0.854 1.27 157.40 <0.0001

diameter shade 0.384 0.0486 1.232 0.0886 0.706 1.26 62.41 <0.0001 0.5363

sun 0.342 0.0451 1.124 0.0858 0.681 1.27 57.66 <0.0001

blade area shade 0.832 0.0511 1.827 0.0862 0.933 1.19 264.87 <0.0001 0.6283

sun 0.801 0.0363 1.797 0.0678 0.963 1.19 487.80 <0.0001

sheath area shade 0.980 0.0391 1.352 0.0659 0.971 1.19 629.12 <0.0001 0.8553

sun 0.990 0.0425 1.495 0.0793 0.966 1.19 544.01 <0.0001

leaf number shade 12.783 17.470 1.492 31.871 0.673 1.26 53.54 <0.0001 0.3888

sun 15.614 28.098 2.532 53.507 0.534 1.27 30.88 <0.0001

BAI shade )0.007 0.0391 0.333 0.0659 0.002 1.19 0.03 0.8561 0.0396

sun )0.109 0.0268 0.528 0.0500 0.466 1.19 16.60 0.0006

SBA shade )0.163 0.0397 2.044 0.0670 0.471 1.19 16.90 0.0006 0.4278

sun )0.125 0.0263 1.926 0.0492 0.542 1.19 22.45 0.0001

SShA shade )0.254 0.0460 2.293 0.0776 0.616 1.19 30.46 <0.0001 0.0816

sun )0.158 0.0259 2.181 0.0483 0.663 1.19 37.45 <0.0001

BAR shade )0.168 0.0511 1.827 0.0862 0.363 1.19 10.80 0.0039 0.6284

sun )0.199 0.0363 1.797 0.0678 0.613 1.19 30.06 <0.0001

SMF shade )0.078 0.0381 0.444 0.0694 0.140 1.26 4.22 0.0501 0.4216

sun )0.035 0.0369 0.323 0.0703 0.032 1.27 0.90 0.3524

BMF shade )0.037 0.0359 0.951 0.0654 0.039 1.26 1.05 0.3159 0.1266

sun )0.103 0.0214 1.013 0.0408 0.462 1.27 23.17 <0.0001

ShMF shade 0.114 0.0315 0.375 0.0574 0.335 1.26 13.08 0.0013 0.6787

sun 0.129 0.0190 0.434 0.0362 0.632 1.27 46.33 <0.0001

blade sheath ratio shade )2.479 0.5870 6.815 10.709 0.407 1.26 17.84 0.0003 0.0120

sun )0.849 0.1197 3.038 0.2279 0.651 1.27 50.35 <0.0001

projected area shade 0.841 0.0549 1.494 0.1001 0.900 1.26 235.11 <0.0001 0.8714

sun 0.853 0.0418 1.326 0.0796 0.939 1.27 415.77 <0.0001

maximum tank water

content

shade 0.972 0.0700 0.493 0.1277 0.881 1.26 192.73 <0.0001 0.1021

sun 1.129 0.0623 0.526 0.1186 0.924 1.27 328.98 <0.0001

water content by leaf shade 0.576 0.1155 0.076 0.1947 0.567 1.19 24.89 <0.0001 0.1205

sun 0.803 0.0813 )0.103 0.1519 0.837 1.19 97.45 <0.0001

actual tank water

content

shade 1.005 0.2544 )1.114 0.4640 0.375 1.26 15.63 0.0005 0.2694

sun 1.458 0.2574 )0.974 0.4901 0.544 1.27 15.77 <0.0001

maximum evaporative

area

shade 0.791 0.0751 0.114 0.1267 0.854 1.19 110.82 <0.0001 0.9747

sun 0.788 0.0589 0.357 0.1100 0.904 1.19 179.09 <0.0001

number of evaporative

areas

shade 0.128 0.0409 0.360 0.0691 0.339 1.19 9.77 0.0056 0.9697

sun 0.129 0.0216 0.439 0.0403 0.656 1.19 36.19 <0.0001

evaporative area by leaf shade )0.007 0.0251 )0.039 0.0423 0.004 1.19 0.08 0.7767 0.1512

sun )0.049 0.0136 0.010 0.0254 0.412 1.19 13.32 0.0017

Habitat and size-related effects on bromeliad morphology Cavallero, Lopez & Barberis

390 Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands

Appendix 1. Continued.

variable habitat

biomass

estimate

biomass

error

intercept

estimate

intercept

error R2 df F P-value

Habitat

· biomass

water content per evaporative

area ratio

shade 0.143 0.0863 0.427 0.1455 0.126 1.19 2.75 0.1139 0.0887

sun 0.329 0.0605 0.179 0.1130 0.609 1.19 29.55 <0.0001

BAI = blade area index; BAR = blade area ratio; SBA = specific blade area; SShA = specific sheath area; BMF = blade mass fraction;

ShMF = sheath mass fraction; SMF = stem mass fraction. Values show biomass estimates and standard errors, intercept estimates and standard

errors, R2 = regression coefficient, df = numerator, denominator degrees of freedom, F value, P = significance level. Habitat · biomass interaction

values lower than 0.05 indicate that the slopes of regression curves were not homogeneous. The analyses were carried out with SAS 8.0 version.

Cavallero, Lopez & Barberis Habitat and size-related effects on bromeliad morphology

Plant Biology 11 (2009) 379–391 ª 2008 German Botanical Society and The Royal Botanical Society of the Netherlands 391