ORIGINAL ARTICLE

Ulo Niinemets

Energy requirement for foliage construction depends on tree size

in young Picea abies trees

Received: 9 April 1996 / Accepted: 14 January 1997

AbstractmThe relationship between stand biomass produc-tion, and tree age and size is generally a curve with amaximum. To understand why wood production decreasesin the final stages of stand development, the influence ofincreasing tree size on foliage chemical composition andsubstrate requirement for foliage construction in terms ofglucose [CC, g glucose (g dry mass)–1] was investigated inthe evergreen coniferPicea abies(L.) Karst. Because it wasalready known that irradiance affects both foliage morphol-ogy and chemistry in this species, and it was expected thatthe foliage in large overstory trees would intercept onaverage more light than that in saplings in understory,irradiance was measured in the sampling locations andincluded in the statistical models. CC of needles increasedwith increasing total tree height (TH) and was independentof relative irradiance. A major reason for increasing CCwith increasing TH was a greater proportion of carbon-richlignin in the needles in large trees. However, lignin did notfully account for the observed changes in CC, and it wasnecessary to assume that certain other carbon-rich second-ary metabolites such as terpenes also accumulate in thefoliage of large trees. Enhanced requirements for needlemechanical strength as evidenced by greater lignin concen-trations in large trees were attributed to increased waterlimitations with increasing tree height. Because waterrelations may also control the sink capacities for assimilateusage, apart from the mechanical requirements, they mayprovide an explanation for the accumulation of otherenergetically expensive compounds in the needles as well.Biomass partitioning within the shoot was another foliarparameter modified in response to increasing tree size. Theproportion of shoot axes, which serve to provide needleswith mechanical support and to supply them with water,

decreased with increasing TH. This may limit water avail-ability in the needles, and/or manifest a lower waterrequirement of the needles containing proportionally moresupporting and storage substances, and consequently, lessphysiologically active compounds such as proteins. Proba-bly the same factors which caused CC of the needles todepend on TH, were also responsible for greater CC of theshoot axes in larger trees. These results collectively suggestthat increasingly more adverse water relations with increas-ing tree size may provide a mechanistic explanation for thedecline in foliar biomass and its functional activity duringstand ageing.

Key wordsmCarbon concentration? Construction cost?Irradiance? Lignin concentration? Needle morphology

Introduction

It has long been known that stand biomass production is notconstant in time, but is rather a curve with a maximum(Moller et al. 1954; Whittaker and Woodwell 1967; Jarvisand Leverenz 1983; Ryan and Waring 1992). Increasingfoliar biomass and area with increasing tree size provide asimple explanation of why stand biomass accumulationincreases up to canopy closure. However, it is still notclear why tree productivity declines in the other end ofstand development (Yoder et al. 1994). There has been awide consensus that respiratory costs increase with increas-ing stand age (Waring and Schlesinger 1985; Ryan andWaring 1992 and references therein) and cause net standproduction to decline. However, recent evidence is not inline with this argument (Ryan and Waring 1992). Rather itappears that declining rates of carbon assimilation may beresponsible for levelling off and ceasing of growth in largetrees, where (1) stomatal limitation of photosynthesis isgreater (Donovan and Ehleringer 1992; Yoder et al. 1994),and (2) even at constant CO2 in the intercellular spaces thephotosynthesis is lower than that in small and young trees(Kull and Koppel 1987; Schoettle 1994; Niinemets 1997).

U. NiinemetsLS Pflanzeno¨kologie II, BITOK, Universitat Bayreuth,Postfach 10 12 51, D-95440 Bayreuth, Germany

Present address:Estonian Institute of Ecology,Riia 181, Tartu EE 2400, Estonia

Trees (1997) 11: 420–431 Springer-Verlag 1997

The effect (1) has been attributed to higher resistances towater flow in stems of tall trees (Yoder et al. 1994). Giventhat the leaves subject to a more severe water stress alsorequire a greater fractional investment of foliar biomass insupporting structures, which would dilute photosyntheticmachinery in the leaves, the effect (2) may as well resultfrom increased water limitations. InPicea abies, foliagecarbon concentration increased and nitrogen concentrationdecreased with increasing total tree height (Niinemets1997). Niinemets (1997) assumed that this reverse correla-tion between foliar nitrogen, which scales positively withfoliage photosynthetic capacity (Field and Mooney 1986),and carbon, which depends on the content of carbon-richcompounds such as lignin (Van Soest 1963), explains whyphotosynthetic capacity decreases with increasing tree sizein this species (Kull and Koppel 1987). However, itremained unclear whether higher carbon concentrationsare attributable to changes in lignin concentration orwhether some other carbon-rich metabolites accumulateand dilute the concentration of photosynthetic machinery.This distinction appears relevant, because water limitationsmay have increased the carbon concentration in large treeseither by increasing the investment in carbon-expensivechemicals such as lignin, responsible for foliage mechanicalstrength, or by decreasing carbon translocation from theneedles by lowering the sink capacities for assimilate usage.

Apart from the photosynthesis, both total foliar biomass(Ovington 1957; Oshima et al. 1958) and the fraction ofannual biomass invested in foliage (Whittaker and Wood-well 1968) decrease in older trees. This is thought to resultfrom disproportionately increasing biomass costs for woodysupport tissue in stems and roots: the investments, whichare essential to cover the enhanced requirements formechanical stability of tree stems with increasing size(Givnish 1988). However, biomass is not necessarily anestimate of the energy investments for foliage formation.Inasmuch as foliar carbon concentration is a major deter-minant of the glucose cost of foliage construction (CC;Vertregt and Penning de Vries 1987; Poorter 1994), increas-ing carbon concentration of foliage with increasing tree sizein P. abies(Niinemets 1997) suggests that foliar biomassmay also decline with increasing tree size due to greatercarbon and energy requirements for its formation. More-over, the extra glucose invested in foliage constructioncannot be used to construct further foliage, and thus, highCC affects the photosynthate available for growth morethan is necessarily evident in the amount of the additionalcarbon that has been paid for foliage formation (Poorter1994). Unfortunately, conclusions on CC cannot be drawnalone from the foliage carbon concentration, because thelumped variables such as carbon and energy contents areless informative than the tissue biochemical composition is,and do not provide directly an estimate of CC.

In this paper the data for the evergreen coniferPiceaabies reported by Niinemets (1997) were further analysedaddressing the following questions: (1) What causes foliagecarbon concentration to increase with increasing tree size?(2) Do needle and shoot construction costs depend on treesize? Inasmuch as needles are clumped to shoots, a conifer

shoot behaves effectively as a leaf in broad-leaved species(Leverenz and Hinckley 1990). In light of the recentevidence suggesting that biomass partitioning within theshoot is dependent on tree size inP. abies(Niinemets andKull 1995b), and that the construction costs for assimilativeand non-assimilative structures may be different (Poorter1994), it was necessary to consider the supporting biomasswithin the shoot as well. From this analysis I hoped to gainimportant and mechanistic insight into stand-level ontoge-netic processes. Since light availability also influencesfoliage chemical composition (Waring et al. 1985; Niine-mets 1995, 1997), and foliar biomass declines with increas-ing stand age (Ovington 1957; Oshima et al. 1958) resultingin greater irradiances within the canopy of older trees, thevariation of foliar chemistry and structure with irradiancewas also studied.

Materials and methods

Study area and foliage sampling

The study was accomplished in a forest dominated byP. abies atOberwarmensteinach (49°599 N, 11°479 E; elevation approx. 760 mabove sea level), Fichtelgebirge, Germany in the middle of September1991. The stand was located on a plateau-like crest of a hill withpodzolic and brown pseudopodzolic soils formed on phyllite(Hantschel 1987; Oren et al. 1988; Tu¨rk 1992). Extensive researchon forest decline due to soil acidification has been previously con-ducted in the vicinity of the studied stand in Oberwarmensteinach(Oren et al. 1988; Schulze et al. 1989). The current work was carriedout at the “undamaged” site, where no injury symptoms such as needlechlorosis or premature needle abscission were detectable (see Weikertet al. 1989).

Foliar samples were taken from terminal crown positions in thesouth aspect of five variously-exposed trees. Total height of sampledtrees (TH, m) ranged from 2.3 to 16.7 (mean+ SE = 8.9+ 1.0), andtree age (years), which was estimated from the increment cores at1.3 m, from 12 to 32 (21.4+ 1.3). To ensure sampling across a verticallight gradient, the foliage was collected at seven to twelve differentcanopy heights. The highest relative sampling height, i.e. height in thetree per TH, was never less than 0.92. Every sample consisted of threeto eight shoots. Foliar sampling was restricted to between 1500 and1600 hours on cloudy days. A more detailed sampling scheme is givenin Niinemets (1997).

Relative irradiance (RI) of the sampling locations

A hemispherical photographic technique (Anderson 1964) as modifiedby Nilson and Ross (1979) was used to describe the variation in RI.Several photographs per sampling location were taken immediatelyafter foliage sampling, relative area of canopy gaps with respect tozenith angle was measured from every photograph, corrected for cosineof incidence effects and diffuse site factor (relative amount of pene-trating diffuse solar radiation) was calculated. Thus, RI is an indexwhich varies from 0 to 1. RI = 1.0 corresponds to diffuse irradianceabove the stand, and RI = 0.0 to complete shade with no penetratingcanopy gaps. No correction factors for direct solar radiation wereintroduced, because the azimuth of sampling locations was constant.

Foliage chemical composition and heat of combustion

Foliar carbon (Cm) and nitrogen (Nm) concentrations were estimatedwith a C/N analyser (Model 1500, Carlo Erba, Italy). Concentration ofnon-structural carbohydrates (ethanol-soluble carbohydrates plus

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starch, TNC) was determined by anthrone reaction as describedpreviously (Niinemets 1995, 1997). Energy content of samples (heatof combustion) was estimated with a microbomb calorimeter (MBK-2,SKB, Tartu, Estonia; Loˆhmus et al. 1983). Initially duplicate subsam-ples were analysed, if the difference between them was more than2.5%, a third sample was analysed. Ash content was estimatedseparately after combustion the sample in a muffle furnace at 500°Cfor 3 h, and caloricity was expressed per mineral-free dry mass, takingthe fraction of minerals in ash equal to 0.67 (Vertregt and Penning deVries 1987). Acid insoluble lignin was determined gravimetricallyaccording to the micromethod of Effland (1977). Prior to the acidichydrolysis, samples were extracted with 100% acetone, 96% ethanol,and ethanol: benzene solution (1:2, v/v) at 40°C to remove the acidinsoluble extractives. The solution was mixed frequently during theextraction, and the solvent replaced every hour. The extraction wascontinued with each solvent until the residue did not alter the colour ofthe extraction solution, but was repeated at least four times. Aftercorrecting for residual ash content, lignin content was calculated perunit total dry weight (Lm).

Foliar morphology. Parameters for NSC-free leaf dry mass

Total needle surface area was calculated from needle geometricalmeasurements according to Niinemets and Kull (1995a). Dry mass ofall foliage components was estimated after drying the samples at 70°Cfor at least 48 h.

The size of foliar non-structural carbohydrate (NSC) pool isextremely variable on a diurnal (Fondy et al. 1989; Servaites et al.1989) and a seasonal (Amundson et al. 1991; Gholz and Cropper 1991;Linder 1995) basis. This variability results in a parallel variation infoliar dry mass per area (Chatterton et al. 1972) and in a dilution of theconcentrations of other leaf components (Plha´k 1984). Moreover, avertical gradient in daily photosynthetic production, and consequentlyin NSC, also exists across the canopy due to differences in irradiance(Niinemets 1995, 1997). Thus, in many cases the conclusions arerobuster and safer if established with the quantities expressed on aNSC-free dry mass basis. The calculation of foliage chemical variablesfor the NSC-free dry mass follows Niinemets (1995, 1997) and isbriefly described here. Lm and Nm were divided by 1-TNC (TNC isexpressed here as the proportion of dry matter) to obtain leaf nitrogen(Nmc) and lignin (Lmc) concentrations of NSC-free dry mass. Foliarcarbon concentration of NSC-free dry mass was calculated as:

Cmc�

Cm ÿ NCC1 ÿ TNC

; �1�

where NCC is the proportion of leaf carbon in NSC.

Construction cost

Leaf construction cost [CC, g glucose (g dry mass)–1] may either becalculated from mineral-free heat of combustion (∆Ha, kJ g–1) and Nm

(g g–1) (Williams et al. 1987) or from mineral-free carbon concentra-tion (Cma, g g–1) and Nm (Vertregt and Penning de Vries 1987; Poorter1994). Insofar as both∆Ha and Cma [Cma = Cm/(1-M), where M ismineral concentration] were available, CC could be calculated in bothways (CCh and CCc denote the construction costs calculated from∆Ha

and from Cma, respectively). Since nitrogen reduction requires aconsiderable amount of extra metabolic energy, which is not readilyexpressed by the heat of combustion or by the carbon concentration ofthe organic compounds, the concentration of organic nitrogen forms anintegral part of the equations for CC calculation. However, as theseregression equations stand (Williams et al. 1987; Poorter 1994) it ispossible to use either ammonium or nitrate as nitrogen source. Also, ithas not yet been taken into account that the carbon costs for nitratereduction depend on where it goes on in the plant. Nitrate reduction inleaves during a light period may proceed with no glucose cost, sincethe reductive equivalents generated in chloroplasts in light maydirectly be used for nitrate assimilation (Robinson 1988; Weger et al.1992). To account for the differences in the cost of nitrate reductionamong various plant organs, and for the very common situations in

natural communities, where a range of nitrogen substrates differing inoxidation state are available, all equations were reformulated to includea new parameter, Pn, the fraction of organic nitrogen in a given tissue,originating from nitrate reduced in non-assimilative plant parts (Ap-pendix). Thus, the equation of Williams et al. (1987) becomes:

CCh �1Eg

��0:069584Ha ÿ 0:065��1 ÿ M� � 180:15

5PnNm ÿ 3�1 ÿ Pn�Nm

14:0067� 24

�;(2)

where Eg is the growth efficiency term, i.e. the fraction of glucose costretained in the substrate. Estimation of Eg requires very detailedinformation on the chemical composition of leaves including allmajor compound classes. Since the biochemical information in suchdetail was not available, and in general Eg varies little (Williams et al.1987), a value of 0.89 was used (Williams et al. 1987, 1989). As afurther modification, mineral content was used instead of ash-contentin Eq. 2.

Taking the cost of nitrate reduction as four mol reductive equiva-lents per one mol nitrate, and 0.0833 mol glc as the cost of one molNAD(P)H, gives CCc as:

CCc � CC0 �1 ÿ M� �

�4� 180:25� 0:0833 PnNm

14:0067

�; �3�

where CC9, the construction cost of biomass if ammonium is the onlysource of nitrogen (or if all nitrate is assimilated in leaves), is equal to5.077Cma–1.041 (Poorter 1994) or to 5.39Cma–1.191 (Vertregt andPenning de Vries 1987). The second term of Eq. 3 adds additional costsrequired for nitrate reduction. Pn of 0.13 was used for the needles and0.21 for the shoot axes (Appendix). As expected, CCc-s calculated bythe equations of Poorter (1994) and Vertregt and Penning de Vries(1987) were highly correlated (for the whole materialr2 = 1.00,P 5 0.001, N = 66). However, the equation of Poorter (1994) gaveconsistently slightly lower values (1.534+ 0.006, mean+ SE) thanthe other one (1.544+ 0.006) (means were significantly different atP 5 0.001 according to pairedt-test). Since the equation of Poorter(1994) is based on most recent calculations and includes manysecondary carbon-rich compounds such as several terpenoids, whichmay play a significant role in conifers, this equation was usedthroughout the current study. Foliage construction cost of NSC-freedry mass, CCcc, was calculated according to Eq. 3, using the values ofCma, M and Nm, which were previously calculated for a NSC-free drymass.

Data analysis

Linear correlation and regression techniques were used to test theinfluence of TH and RI on foliage chemical composition and con-struction costs. Differences between the needles and shoot axes inP.abiesas well as between various estimates of construction cost wereseparated by pairedt-test. Statistical relationships were compared byone-way covariation analysis. All differences were considered signif-icant atP5 0.05 (Wilkinson 1990).

Results

Comparison of different estimates of foliage constructioncost

Mineral-free heat of combustion and mineral-free carbonconcentration were positively correlated in both needlesand shoot axes (Fig. 1). Therefore, the estimates of con-struction cost based on Eqs. 2 and 3 were also stronglycorrelated (r2 = 0.48,P 5 0.001 for the whole material).The equation of Williams (1987; Eq. 2) underestimated CC(mean+ SE = 1.511+ 0.005) in comparison to the one ofPoorter (Eq. 3; 1.534+ 0.006). Nevertheless, the differ-ence between the means, though statistically significant

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(P5 0.001), is only approximately 1.5%. It was importantto consider the mineral content of foliage in the calculationsof foliar CC, because there was a good positive correlationbetween M and Nm (r2 = 0.60,P5 0.001). This correlationwould have confused the relationships, if it had not beenaccounted for.

The slope of∆Ha vs Cma for the needles did not differsignificantly from that for the shoot axes (Fig. 1,P4 0.2).Since in Eq. 3 the glucose costs for the construction oforganic compounds are directly regressed to their carbonconcentration, this equation does not require a separateestimation of Eg. Given that more material was also avail-able for foliar carbon concentration than for heat of com-bustion, in further analysis Eq. 3 was used. Nevertheless,since both estimates of CC were correlated, the conclusionsbased on Eqs. 2 and 3 were qualitatively identical.

Differences in CC between needles and shoot axes

Due to higher carbon concentrations of the shoot axes(P 5 0.02, Table 1), their mean construction cost wasalso higher than that of the needles (P 5 0.05, Table 1).

However, both carbon concentrations and constructioncosts of NSC-free dry mass were not significantly differentbetween the needles and the shoot axes (P 4 0.5). Thus,higher CCc of the shoot axes was mainly the result of theirlower (P 5 0.001) concentration of non-structural carbo-hydrates, which contain less carbon (40% for glucose and44.4% for starch) than the foliage on average (Table 1). Theconcentration of carbon-rich lignin was higher in both totaland NSC-free dry mass in the shoot axes, but nitrogenconcentrations were higher in the needles (Table 1). Theconcentration of organic nitrogen per se had little effect on

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Table 1mDifferences in foliage chemical composition and construction cost between needles and shoot axes

Symbol (units) Explanation Mean+SEa

needles shoot axes

∆H (kJ g–1) Heat of combustion 20.31+0.06a 20.48+0.12a∆Ha (kJ g–1) Mineral-free heat of combustion 20.73+0.06a 20.83+0.12aCm (%) Carbon concentration 49.93+0.13a 50.38+0.21bCmc (%) Cm of non-structural carbohydrate

(NSC) free dry mass51.58+0.20a 51.54+0.26a

CCh (g glc g–1) Construction cost (Eq. 2) 1.502+0.005a 1.523+0.010bCCc (g glc g–1) Construction cost (Eq. 3) 1.523+0.006a 1.546+0.010bCCcc (g glc g–1) CCc of NSC-free dry mass 1.613+0.010a 1.604+0.013aLm (%) Lignin concentration 29.9+0.5a 34.8+0.8bLmc (%) Lm of NSC-free dry mass 35.7+0.7a 39.4+0.9aM (%) Mineral concentration 2.12+0.14a 1.96+0.12bNm (%) Nitrogen concentration 1.435+0.037a 1.1+0.05bNmc (%) Nm of NSC-free dry mass 1.696+0.033a 1.25+0.06bTNC (%) Total NSC concentration 16.0+0.5a 12.7+0.4b

a Means with the same letter are not significantly different (pairedt-test)

Fig. 1mRelationships between mineral-free heat of combustion andmineral-free carbon concentration (Cma) in the foliage of P. abies.Intercepts denoted by* do not differ significantly from zero

Fig. 2mDependence of needle construction cost (A) and lignin contentper total needle dry mass (B) on total needle dry mass per area, LMA.Needle construction cost was calculated from needle carbon andnitrogen concentrations according to Eq. 3

CC, since most of foliar nitrogen was either already takenup in reduced form or was reduced in the needles (cf.Appendix). Due to relatively low foliar nitrogen concentra-tions (Table 1), the variability in CC was dominated bychanges in carbon concentration even if the upper boundaryfor the costs of nitrogen reduction (nitrate as the onlynitrogen substrate reduced in non-assimilative plant com-partments) was assumed. Since nitrogen provides also anestimate of foliar protein content, and proteins are richer incarbon (53.5%, Vertregt and Penning de Vries 1987) thanthe foliage on average (Table 1), higher nitrogen concen-tration of the needles (Table 1) may have balanced greaterlignin concentration of the shoot axes, resulting in aconstant Cmc for the whole shoot (Table 1).

Dependence of CC on needle structure and chemicalcomposition

CCc increased with increasing needle dry mass per area(LMA, Fig. 2A). Since leaf nitrogen concentration de-creased (Niinemets 1997), but lignin (Fig. 2B) and NSCconcentrations (Niinemets 1997) increased with increasingLMA, the variation in CCc was further examined withrespect to leaf chemical composition. It appeared thatCCc increased with increasing NSC (r2 = 0.35,P5 0.001)and lignin concentrations (r2 = 0.43, P 5 0.001), butdecreased with increasing Nm (r2 = 0.60, P 5 0.001).The positive correlation between CCc and NSC concentra-tion most likely results from a covariation between thesevariables, because due to low energy requirement forconstruction (1.000 g glc g–1 for glucose and 1.173 g glc

g–1 for starch; Williams et al. 1987) NSC actually di-minishes CC. The calculation of lignin and nitrogen con-centrations per NSC-free dry mass improved the relation-ships somewhat (Fig. 3A, B).

Lignin concentration was also positively correlated withcarbon (Fig. 4A) and NSC concentrations (Fig. 4B), andnegatively with nitrogen concentration (Fig. 4C), highlight-ing the major influence of lignin concentration on CC.Based on the information depicted on Figs. 3 and 4, it isnow possible to conclude that the covariation of NSC andnitrogen concentrations with lignin concentration deter-mines whether the slope of the relationships of CC vsNSC, and CC vs Nm is positive or negative.

Influence of relative irradiance and tree size on CC

Both CC of total and NSC-free needle dry mass increasedwith increasing total height, but were independent ofrelative irradiance (Table 2). This pattern was paralleledby a variability in lignin concentration. Lm was constantacross the light gradient and increased with increasing TH(Table 2). TH and construction cost of shoot axes were alsocorrelated (r2 = 0.23, P 5 0.005 for CCc and r2 = 0.28,P 5 0.001 for CCcc). When shoot construction cost wascalculated as a weighed mean of the construction costs ofneedles and shoot axes, it appeared that RI also significant-

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Fig. 3mCorrelations between needleconstruction cost of non-structuralcarbohydrate (NSC) free dry mass,CCcc, and needle lignin (A) and ni-trogen contents (B) per NSC-free drymass (Lmc and Nmc, respectively).NSC is the sum of ethanol-solublecarbohydrates and starch

Fig. 4mNeedle lignin content per NSC-free needle dry mass independence on needle carbon content per NSC-free dry mass (A),NSC concentration (B) and on Nmc (C)

ly affected CC (Table 2). This effect of RI on shootconstruction cost resulted from the positive correlationsbetween CCc and CCcc of the shoot axes and RI (r2 = 0.28,P5 0.001 for both CCc and CCcc).

Since the mass ratio of shoot axis to the needles on theshoot, Ms/Mn, increased with increasing RI and declinedwith TH (Table 2), the patterns of biomass partitioningwithin the shoot also affected the construction cost of theshoot. Moreover, foliage chemical composition and Ms/Mn

were not independent of each other. The fractional invest-ment of shoot biomass in shoot axis increased with increas-ing needle nitrogen concentration (Fig. 5A) and decreasedwith increasing needle carbon concentration (Fig. 5B).These patterns were qualitatively the same with shootnitrogen and carbon concentrations (calculated as weighedmeans;r2 = 0.43,P5 0.001 for shoot nitrogen andr2 = 0.20,P 5 0.01 for shoot carbon), and with nitrogen concentra-tion of the shoot axes (r2 = 0.28, P 5 0.001). However,neither carbon nor lignin concentrations of the shoot axesand Ms/Mn were correlated. Thus, the fraction of shootbiomass necessary for needle support, was not altered bychanging the concentration of compounds increasing themechanical strength of the supporting tissues.

Discussion

Determination of construction costs

Consistent with the previous work (Lafitte and Loomis1988; Walton et al. 1990), both the heat of combustion(Eq. 2; Williams et al. 1987) and carbon concentrationmethod (Eq. 3; Vertregt and Penning de Vries 1987; Poorter1994) gave very similar estimates for foliage constructioncost in P. abies(Table 1). However, the lumped variablessuch as heat of combustion or carbon concentration lackmuch information, which would be available if the biomasschemical composition were known (Lambers et al. 1990).Fortunately, the fraction of substrate electrons and carbonatoms retained in the product is extremely conservativeamong plants (McDermitt and Loomis 1981; Vertregt andPenning de Vries 1987; Williams et al. 1987; Walton et al.1990), and therefore the correlative approaches generallygive results which are in good agreement with those derived

from the biochemical pathway analysis (Williams et al.1987; Lafitte and Loomis 1988; Poorter 1994). The growthefficiency term (Eg, Eq. 2) is still variable (Williams et al.1987; Lafitte and Loomis 1988), to get the same mean CCwith both the heat of combustion and carbon concentrationmethods, an Eg of 0.90 rather than 0.89 should have beenused in Eq. 2 forP. abies.

The reduction state of inorganic nitrogen substrate maycrucially influence the calculation of CC. The significanceof nitrogen term in Eqs. 2 and 3 is illustrated by a study innitrogen-fertilised and unfertilised seedlings ofPinus taeda(Griffin et al. 1993). The heat of combustion differed littlebetween the treatments in that study, but since nitrate wasthe only source of organic nitrogen in the needles, theneedles in fertilised seedlings with significantly higher Nm

had also higher CC. Exact estimation of nitrogen reductioncosts is also important in the foliage ofP. abies, where Nm

decreased with increasing LMA and was negatively relatedto Cm (Niinemets 1997). Despite the extensive and broadinformation on nitrogen nutrition inP. abiesat the studylocation, a number of assumptions were necessary to derivethe proportion of foliar nitrogen, which originates fromnitrate reduction in non-assimilative organs (Appendix).The existing data supported the view that only a minorpart of needle nitrogen is reduced in the non-photosynthetictissues. Due to low nitrogen concentrations in the needles

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Table 2mDependencies of dry matter partitioning within the shoot,foliage construction cost and lignin concentration on total tree height(TH, m) and relative irradiance (RI): multiple linear regression analysis

Variablea Interceptb Slopes

TH P RI P r2 N

Ms/Mn 0.40 –0.016 0.001 0.258 0.02 0.44 45CCc 1.49 0.0029 0.001 0.026 n. s. 0.34 40CCcc 1.55 0.0050 0.001 0.070 n. s. 0.48 40CCcm 1.49 0.0023 0.01 0.058 0.05 0.44 36CCcmc 1.55 0.0045 0.001 0.090 0.05 0.56 35Lm 28.0 0.18 0.05 0.47 n. s. 0.19 35Lmc 32.1 0.31 0.01 2.1 n. s. 0.33 35

a Ms/Mn (g g–1) – mass ratio of shoot axes to needles, CCcm (g glc g–1) –shoot construction cost (weighed mean of the construction costs ofneedles and shoot axis), CCcmc – CCcm of NSC-free shoot dry mass.Other variables and units are defined in Table 1b All intercepts are significant atP5 0.001

Fig. 5mMass ratio of shoot axes toneedles vs needle nitrogen (A) andcarbon (B) concentration

and shoot axes (Table 1), the conclusions were not verysensitive to Pn (Eqs. 2, 3) in the current study, and were notqualitatively altered even by using an unrealistic Pn of 1.

The variability in CC with foliar morphology and chemicalcomposition

CC of needles inPinus taeda(1.588 g glc g–1) calculatedfrom biochemical pathway analysis, assuming that ammo-nium is the only nitrogen substrate (Chung and Barnes1977), is somewhat higher than that inP. abies(Table 1). Incontrast to P. abies, the needles were more costly toproduce than the shoot axes inP. taeda(Chung and Barnes1977). Despite higher lignin concentration in the shoot axesin P. taeda, the needles had lower total carbohydrateconcentration (non-structural + cell-wall polysachharides)and greater lipid and protein concentrations (Chung andBarnes 1977). InP. abies, the major reason for the lowerCC of the needles was their greater NSC concentration(Table 1).

Due to a positive effect of irradiance on photosynthesis,NSC concentration is dependent on light conditions withinthe canopy (Servaites et al. 1989; Takahashi et al. 1993).This correlation also alters LMA (Chatterton et al. 1972)and the concentration of other plant metabolites (Niinemets1995, 1997). Higher photosynthesis and thus, greater NSCconcentration of the needles than of the shoot axes providedan explanation for the differences in CC and carbon con-centration between these compartments as well (Table 1).These results signify that the expression of the quantities ona NSC-free dry mass basis provided valuable insight intothe relationships between foliage chemical constituents andCC, and into the dependencies of CC and foliage composi-tion on tree size (Table 2) in the current study.

The scaling of CC with LMA (Fig. 2A) is an expectedresult, because needle carbon concentration and needle drymass per area were positively correlated (Niinemets 1997).The current study also identifies the major biochemicalcompound classes, variation in which with LMA is thecause for the detected relationships between Cm, CC andLMA. In addition to the positive correlation between ligninconcentration and LMA (Fig. 2B), Nm decreases (r2 = 0.60)and TNC increases (r2 = 0.63) with increasing LMAaccording to the former study (Niinemets 1997). SinceNSC has lower CC and carbon content (cf. above) thanthe foliage inP. abieson average (Table 1), it cannot beresponsible for the increases in CC and Cm with LMA. Bycontrast, lignin, containing 65.4% carbon (calculated forP.abiesaccording to Freudenberg 1965), can (Figs. 3A, 4A).A similar positive relationship between cell-wall lignin andcarbon concentrations has previously been established for anumber of herbaceous species as well (Van Soest 1963).However, it remains unclear why nitrogen, which is anestimate of carbon-rich (53.5%) protein concentration, andwhich also requires extra glucose for assimilation (Eqs. 2,3), is negatively related to CC (this study) and carbonconcentration (Niinemets 1997). Niinemets (1997) specu-lated that Cm gives an estimate of lignin-rich supporting

tissues, and that Cm and Nm are negatively related, becausethe supporting tissues dilute the assimilative ones. Thecurrent study supports this argument (Fig. 4C).

Now, as it has become evident that lignin has a majorinfluence on CC and Cm, a question arises if the changes inneedle lignin content are sufficient to account for thevariability in needle carbon and CC with LMA and treedimensions (cf. below). As carbon concentration per NSC-free dry mass varies from 45 to 55%, lignin concentrationon the same basis is expected to vary from approximately19 to 43% (Fig. 4A). However, given the carbon concen-tration of lignin in P. abies (65.4%, Freudenberg 1965),lignin concentration should vary from approximately 19 to59%, if it were the only source of the changes in carbonconcentration. Thus, it appears that a variability in severalother carbon-rich compounds is also responsible for theobserved differences in CC and Cm.

Needle CC does not depend on irradiance inP. abies

Acclimation to long-term differences in water availabilityincludes changes in cell wall composition and in theproportion of supporting structures in the foliage (Myerset al. 1987; Rascio et al. 1990; Fredeen et al. 1991).Because evaporative demand scales positively with irradi-ance, foliar water potentials become increasingly morenegative with increasing irradiance (Myers et al. 1987).This means that the requirements for foliage mechanicalsupport should also scale with irradiance. In several decid-uous species, both foliar lignin (Kausch and Haas 1966;Waring et al. 1985) and carbon concentrations (Niinemets1995) are greater at higher light. This may cause CC todepend on light environment as well. There is evidence thatCC in needles ofP. abiesmay be related to irradiance. Inthis species,∆H was higher in sun (20.55 kJ g–1) than inshade needles (20.12 kJ g–1; Frey and Ivask 1983); for thesun needles even values as high as 20.79 kJ g–1 have beenmeasured (Runge 1986). However,∆H is not an immediateestimate of construction cost, because it is calculated pertotal rather than per mineral-free dry weight, and it does notinclude the nitrogen assimilation costs (Eq. 2). The positivecorrelation between foliage mineral and nitrogen concen-trations observed in the current study further complicatesthe comparison. When all these confounding effects wereaccounted for, it appeared that CC of needles was indepen-dent of irradiance (Table 2). This constancy of CC acrosslight gradients seems to be more general. In seven tropicalrain-forest species, CC was positively correlated withirradiance in only two (Williams et al. 1989), and CC wasindependent of irradiance in another rain-forest speciesAlocasia macrorrhiza(Sims and Pearcy 1991). BecauseNSC concentration is also positively affected by irradiance,changes in NSC may offset the light-related variability inlignin concentration, and result in the non-correlationbetween CC and irradiance. However, CC and lignin con-centration were independent of irradiance when the changesin NSC were accounted for inP. abies(Table 2).

426

Larger trees have costlier needles inP. abies

The variability in tree size provided an explanation for thedifferences in CC and lignin concentration (Table 2). In-creasing water stress with increasing tree size has beenspeculated to play a central role in modifying foliar mor-phology (Kull and Niinemets 1993; Niinemets 1995; Nii-nemets and Kull 1995a) and chemical composition (Niine-mets 1997). This hypothesis receives solid support from astudy in Picea sitchensis, where the gradients of waterpotential up to 0.2 MPa m–1 have been measured in thestems (Hellkvist et al. 1974). The magnitude of thesegradients is considerably greater than that caused by thegravitational component of water potential (approximately0.01 MPa m–1). Studies comparing stable carbon isotopecomposition of biomass in large vs small trees also con-clude that water limitations play a more crucial part incarbon acquisition in large than in small trees (Donovanand Ehleringer 1992; Yoder et al. 1994). Thus, currentevidence is fully consistent with the hypothesis of enhancedrequirements for foliage mechanical strength due to moresevere water limitations in large trees. Greater supportingdemands may have brought about greater needle ligninconcentrations and increased the costs for foliage construc-tion in P. abies(Table 2).

However, the changes in lignin concentration alone didnot fully account for the differences in needle carbonconcentrations and CC (cf. above). Thus, I hypothesisethat the concentration of certain secondary carbon-richmetabolites in the needles also increases with TH. Thereare two studies to back this assumption. First, in anotherconifer Pinus sylvestristhe proportion of resin ducts inneedle transverse section increases with increasing tree age(Kovalyev 1980); in two extreme situations, in 5- and 100-year-old trees, resin ducts comprise 9 and 16%, respec-tively, of the area of needle transverse section in thisconifer. Second, limited water availability increases thecontent of monoterpenes inP. abies (Kainulainen et al.1992). There was also a tendency of certain terpenes toincrease and the pools of others to stay constant in responseto short-term water stress inCupressus sempervirens(Yaniet al. 1993). However, as stress continued, terpenes werereadily metabolised helping the plants to survive the ad-verse conditions (Yani et al. 1993). Thus, increased con-centration of secondary substances may be an importantfactor increasing the safety margin for severe water stress inlarge trees ofP. abies.

From another perspective, sink capacities for assimilateusage may also control foliage composition. Usually starchand other carbohydrates accumulate in response to excesssource abilities to supply photosynthate, but also lignin,condensed tannins and terpene resins may accumulate(Chapin et al. 1990). To save storage space, it may bebeneficial to accumulate carbon- and energy-rich com-pounds such as terpenoids (e.g. limonene, a monoterpene,has a carbon content of 88.2%) rather than carbohydrates,the most conventional reserve compounds. In conifers,carbohydrates seem to play a peripheral role in the storage.According to the study of Distelbarth et al. (1984), crude

lipids (including terpenoids) are the most important com-pound class of reserve substances in terms of accumulatedenergy in five conifers, includingP. abies. Thus, increasingproportion of secondary metabolites as well as lignin withincreasing tree size inP. abiesmay also manifest a sort ofassimilate overflow due to lower sink strengths in oldertrees.

Shoot CC in dependence on relative irradiance and tree size

Since the construction costs of both the shoot axes andneedles were positively related to tree size, shoot CCincreased with increasing tree height. Contrary to theneedles, CC of the shoot axes was affected by light, andtherefore, CC of shoots also scaled positively with irradi-ance (Table 2). However, lignin concentrations were inde-pendent of irradiance in both needles and shoot axes.Accordingly, the accumulation of other carbon-rich com-pounds such as terpenes in higher light is probably thereason why CC of the shoot axes was sensitive to irradi-ance. As discussed above, it is likely that water availabilitygradients, accompanying the light gradients across thecanopy, rather than irradiance per se caused these modifica-tions in the chemical composition of the shoot axes.Because tissue water relations influence the expansiongrowth (Dale 1988), the accumulation of carbon-rich com-pounds exported from the needles to the shoot axes mayhave resulted from greater water restrictions imposed ongrowth in higher irradiance.

Increased mass ratio of needles to branches inPinussylvestris (Kellomaki 1981) or to shoot axes inAbiesmariesii (Kohyama 1980),Pinus taeda (Cregg et al.1993) andP. abies(Table 2) in lower irradiance suggeststhat shading shifts the balance between the production ofneedles and needle-supporting branches. There exists abasic relationship between the amount of supported needlesand the capacity of xylem to supply water to them (Grierand Waring 1974; Ryan 1989). Thus, the greater proportionof shoot axis biomass within a shoot at higher irradiancemay directly be related to greater water requirements there.Since foliar nitrogen is a good estimate of foliage physio-logical activity and water demand (Schulze et al. 1994), andfoliar carbon of fractional investment in supporting struc-tures and storage compounds (this study), this hypothesis isfurther advocated by the positive relationship of Ms/Mn

with needle nitrogen (Fig. 5A) and by the negative onewith needle carbon concentration (Fig. 5B).

Xylem anatomy changes (Rundel and Stecker 1977) andthe fraction of sapwood in stemwood decreases (Sellin1991) with increasing tree size and age. In addition tothese tree size effects altering water transport capacity ofstems, the decrease of Ms/Mn with TH in P. abies(Niine-mets and Kull 1995b, Table 2) and with tree age inPinustaeda (Greenwood 1984) may also imply greater restric-tions to water flow in shoots due to decreased volume ofconductive elements per unit foliar biomass in large trees.Of course, lower values of Ms/Mn, which will result inlower water supply to the needles, may also be balanced by

427

decreased physiological activity and water demand of theneedles in large trees (Niinemets 1997, this study).

In light of the recent work demonstrating greater sto-matal limitation of carbon assimilation (Donovan andEhleringer 1992; Yoder et al. 1994), lower photosynthesisrates at a common CO2 concentration in the intercellularspaces (Kull and Koppel 1987; Schoettle 1994), and greatercost of unit foliar area in terms of foliar biomass (Kull andNiinemets 1993; Niinemets 1995, 1997; Niinemets andKull 1995a) in large than in small trees, the evidence ofgreater foliage construction cost in large trees observed inthe current study adds an additional dimension to size-related alterations in tree productivity. The changes infoliage chemical composition and morphology with treesize are likely to provide a major explanation why the ratesof photosynthesis (Kull and Koppel 1987; Schoettle 1994),the fraction of annual biomass allocated to foliage (Whit-taker and Woodwell 1968; Givnish 1988) and stand foliararea (Leuning et al. 1991; Niinemets and Kull 1995b)decrease with increasing stand age, causing stand growthrates to undergo considerable decline during ageing (Whit-taker and Woodwell 1967, 1968).

AcknowledgementsmThis work was supported by a scholarship of theGerman Academic Exchange Service (DAAD) and by the GermanFederal Minister of Research and Technology (BMFT) under grantBEO 51–0339476A. I am grateful to Indrek Kalamees (EestiLoodusfoto, Tartu, Estonia) for assisting in caloricity estimations andto Prof. John D. Tenhunen (LS Pflanzeno¨kologie II, BITOK, Uni-versitat Bayreuth) for valuable comments on the manuscript.

Appendix

The proportion of foliar nitrogen reduced in non-assimilative plantcompartments

Theory

In calculations of foliar construction cost (Eqs. 2, 3) it is necessary toknow in what stoichiometric proportion various inorganic nitrogensources, with different energy requirements for assimilation, are usedfor foliage formation. In the present analysis only nitrate and ammo-nium (or compounds with equivalent reduction states) are considered,because they are the major inorganic nitrogen substrates in soil andatmospheric deposition at the study area (Hantschel 1987; Tu¨rk 1992;Buchmann 1993). Nevertheless, if more detailed information onnitrogen nutrition were available, then the Eqs. 2 and 3 and the onesformulated here may simply be changed to include a more sophisti-cated treatment of various nitrogen sources. Furthermore, the site ofinorganic nitrogen assimilation is also of importance. In assimilativeorgans, such as leaves, where photosynthetic electron transport mayprovide both CO2 and nitrate assimilation chains with adequate supplyof reducing power (Robinson 1988), nitrogen incorporation intobiomass may proceed with no extra metabolic cost (Raven 1985).Though the carboxylation and photosynthetic electron transport capa-cities are thought to be roughly in balance (e.g. Wullschleger 1993), anestimate of photosynthetic electron transport capacity is usually de-rived from the response-curves of photosynthesis vs intercellular CO2

concentration at saturating irradiance. This estimate will fail to give thetrue value of electron transport in a situation where other electron-consuming processes such as nitrate reduction would go on. Further-more, in a model speciesSpinacia oleracea, CO2 and nitrate assimila-tion did not compete for electrons even at low irradiance (Robinson1988). Robinson (1988) explained the independence of CO2 and nitrate

photoassimilations by different Km values with respect to ferredoxinconcentration of two key enzymes – chloroplastic fructose 1,6-bispho-sphatase and nitrate reductase – the activity of which is regulated byferredoxin concentration in the stroma.

Of course, nitrate reduction in darkened leaves requires mitochon-drial energy supply. Nevertheless, nitrate assimilation rates in leavesduring the dark period are much lower than in light (Weger et al. 1992).Given the aforementioned evidence, the cost of nitrogen assimilation inleaves is assumed to be nil in the current analysis.

In these circumstances, the only nitrogen-dependent component,which adds to foliar construction cost as defined by Eqs. 2 and 3 arisesfrom the nitrate assimilation in photosynthetically incompetent plantcompartments. Thus, it is necessary to know the fraction of organicnitrogen in leaves which originates from nitrate and has been reducedin non-assimilative organs. Simple mathematical conversions give thisproportion for the needles, Pnl, as:

Pn1�

1R1

�R1 ÿ αU1 ÿ βSnUr��Sn�1 ÿ β�

�; �A1�

where Rl is the nitrogen requirement for needle growth per nitrogendemand for annual tree growth; Ul and Ur are the fractions of annualnitrogen uptake by leaves and roots, respectively;α is the fraction offoliar nitrogen uptake that is incorporated into leaf tissues;β is theproportion of nitrate absorbed by roots that is transported to the leavesand reduced there; Sn is the fraction of nitrate in the nitrogen absorbedby roots. The first part of Eq. A1 gives the proportion of leaf nitrogenthat is acquired by roots minus the nitrate that is already reduced inleaves; the second part is the proportion of nitrate in total root nitrogenuptake that is reduced in non-assimilative plant compartments. BothNO2 and NO3– taken up by leaves and incorporated into leaf tissues areassumed to be reduced there. Thus, the present analysis does notseparate these aerial nitrogen substrates from NH4+ and NH3. Incontrast, these atmospheric nitrogen sources differ in metabolic energyrequirements for assimilation in twigs where nitrate reduction isdependent on mitochondrial energy supply. The fraction of organicnitrogen in the shoot axes originating from nitrate assimilation in non-photosynthetic organs, Pns, is given by:

Pns�

1Rs

�γUs

n� �Rs ÿ γUs

nÿ χUs

aÿ δU1�Sn�1 ÿ β�

�; �A2�

where Rs is the ratio of nitrogen in current-year twigs per nitrogendemand for annual tree growth; Us is the proportion of atmosphericnitrogen uptake by current-year twigs per annual nitrogen uptake(superscriptsn anda stand for nitrate and ammonium, respectively);γandχ are the fractions of nitrate and ammonium absorbed by twigs thatare incorporated into twig biomass;δ is the fraction of aerial nitrogenuptake by leaves that is transported to twigs.

Pn determination in Picea abies

Eqs. A1 and A2 signify that the site of inorganic nitrogen uptake is ofconsiderable relevance in determining the metabolic cost for itsassimilation. Though the information for exact estimation of Pnl andPns was missing, approximate estimates were obtained from a numberof published studies as described below.

According to the laboratory experiments,P. abiespreferentiallytakes up ammonium if both ammonium and nitrate are supplied in thesame molar ratio (Berger et al. 1993; Berger 1995). Unfortunately, thedetermination of relative ammonium and nitrate availabilities innatural soils is problematic due to the complex interactions of ammo-nium with soil particles. Ammonium and nitrate ratio in the soilsolution, collected from aP. abiesstand in the vicinity of the currentexperimental plot (Wu¨lfersreuth, Fichtelgebirge), ranged from 1:2 in aH2O extract to 8:1 in a KCl extract (Schmidt et al. 1995). There existsalso a large spatial variability in ammonium and nitrate concentrationsamong the soil horizons, whereas ammonium concentrations declinefaster with increasing soil depth than nitrate concentrations (Hantschel1987; Turk 1992; Buchmann 1993). Studies with15N-labelled NH4+

and NO3– in two P. abies stands in Wu¨lfersreuth (Fichtelgebirge)demonstrated that the actual ratios of ammonium to nitrate uptake lay

428

between 3:1 (Buchmann 1993) and 4:1 (Schmidt et al. 1995). Ex-tensive work has also been conducted (Hantschel 1987; Tu¨rk 1992) onthe seasonal variability of ammonium and nitrogen concentrations inthe soil water at different soil depths in Oberwarmensteinach (currentstudy location) and Wu¨lfersreuth. Annual nitrate inputs to the mineralsoil (litter lysimeter) during 1984–1990 were very similar in bothstands (0.064 mol m–2 year–1 in Oberwarmensteinach and 0.067 molm–2 year–1 in Wulfersreuth), but annual ammonium flux was some-what higher in Wu¨lfersreuth (0.102 mol m–2 year–1) than in Oberwar-mensteinach (0.084 mol m–2 year–1) (Turk 1992). Relying on theaforementioned evidence, a value of 0.25 was assigned to Sn (thenitrate to ammonium ratio in root nitrogen uptake). A value of 0.05 wasfound for Ul using the data of Eilers et al. (1992), giving the NH4+ andNO3– uptake by current-year foliage of 0.019 mol m–2 year–1 (24% oftotal above-ground uptake), and the data of Schulze (1994), reportingthe annual nitrogen requirement for growth inP. abies. α was taken as0.8 (Brumme et al. 1992). Calculating Ur from total above-groundnitrogen uptake (the same data sources), using a value of 0.2 forβ(Gojon et al. 1994), and considering that approximately 25% ofnitrogen required for annual biomass increment is used for foliagegrowth (recalculation of the data of Schulze 1994), Pnl was fixed at0.13. Though the annual nitrate flux (0.086 mol m–2 year–1) in theprecipitation collected above the stand was higher than that ofammonium (0.071 mol m–2 year–1) in Oberwarmensteinach during1984–1990 (Tu¨rk 1992), ammonium rather than nitrate dominatesabove-ground nitrogen uptake inP. abies(Eilers et al. 1992). Consid-ering that about twice as much NH4+ than NO3– is taken up (Eilers et al.1992) gave a Usn of 0.004 and a Usa of 0.008. Bothγ andχ were setequal to 0.8 (Eilers et al. 1992) andδ was found as (1-α )/2. Rs equal to0.23Rl was calculated from the data of the current study. Substitutingthese constants into Eq. A2 gives a value of 0.21 for Pns.

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