Title: Comparison of leaf construction costs in woody species with differing leaf life‐spans in contrasting ecosystems
Abstract: New PhytologistVolume 151, Issue 1 p. 213-226 Free Access Comparison of leaf construction costs in woody species with differing leaf life-spans in contrasting ecosystems Rafael Villar, Corresponding Author Rafael Villar Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Apdo 1095, 41080 Sevilla, Spain; present address: Area de Ecología, Universidad de Córdoba, Colonia San José n°3, 14071 Córdoba, Spain;Author for correspondence: Rafael Villar Tel: +34 957 21 86 35 Fax: +34 957 21 82 33 Email:[email protected]Search for more papers by this authorJosé Merino, José Merino Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Apdo 1095, 41080 Sevilla, Spain; present address: Departamento de Ciencias Ambientales, Universidad Pablo Olavide, Carretera de Utrera Km 1, 41013 Sevilla, SpainSearch for more papers by this author Rafael Villar, Corresponding Author Rafael Villar Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Apdo 1095, 41080 Sevilla, Spain; present address: Area de Ecología, Universidad de Córdoba, Colonia San José n°3, 14071 Córdoba, Spain;Author for correspondence: Rafael Villar Tel: +34 957 21 86 35 Fax: +34 957 21 82 33 Email:[email protected]Search for more papers by this authorJosé Merino, José Merino Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Apdo 1095, 41080 Sevilla, Spain; present address: Departamento de Ciencias Ambientales, Universidad Pablo Olavide, Carretera de Utrera Km 1, 41013 Sevilla, SpainSearch for more papers by this author First published: 21 December 2001 https://doi.org/10.1046/j.1469-8137.2001.00147.xCitations: 166AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract Summary • The construction costs (CC) are reported of leaves from 162 wild woody species from 14 contrasting environments (desert to rain forest) and with different leaf life-spans. • Calorimetric methods were used to estimate the CC of deciduous, semideciduous and evergreen leaves. • Leaf CC showed a wide range (78%) between species, and deciduous species showed a slightly lower CC (6%) than both semideciduous and evergreen species. Mean leaf CC differed between ecosystems, with the highest and lowest CC in the tundra and rain forest, respectively. Leaf CC was positively correlated with lipid concentration. Leaf size (log) and specific leaf area (SLA, leaf area per leaf dry mass) were negatively correlated with leaf CC. Leaf CC did not show differences between different leaf life-spans or ecosystems when leaf size (log) or SLA were included as covariates. • The small differences in leaf CC among leaf life-span types and ecosystems (6% and 23%, respectively) suggest that SLA is more important in determining differences in the carbon balance between species than leaf CC. Leaf size is shown to be an important trait associated with other leaf characteristics. Abbreviations A, ash concentration; CC, construction cost per unit dry mass; CCA, construction cost per unit area; Eg, growth efficiency; Hc, ash free heat of combustion; N, nitrogen; SLA, specific leaf area. Introduction Species with different leaf life-spans differ in many traits related to carbon flux, such as photosynthetic and respiration rates (Mooney & Gulmon, 1979; Field & Mooney, 1986; Reich et al., 1992; Larcher, 1995; Villar et al., 1995; Reich et al., 1997). Fast growing species from favourable habitats show short leaf life-span and have high photosynthetic and respiration rates per unit mass (Poorter et al., 1990; Reich et al., 1992; Atkin et al., 1996; Reich et al., 1997). These differences could help explain the advantages of the different leaf life-spans in different habitats, and thus the distribution of species with different leaf longevity. However, to fully elucidate the advantages in terms of carbon balance of different leaf life-spans in different habitats, we also need to know the energetic costs of tissue construction (i.e. the construction cost, CC). The construction cost includes the glucose required to build carbon skeletons, and the glucose consumed in respiration to supply reductant and ATP for energy-requiring processes in the biosynthesis of the tissue constituents (Penning de Vries et al., 1974; Williams et al., 1987). Although differences in leaf CC among species with different leaf life-span (evergreen and deciduous) have been studied for about three decades, no clear picture has emerged. Early studies suggested that evergreen leaves have higher CC than deciduous ones (Johnson & Tieszen, 1976; Orians & Solbrig, 1977; Miller & Stoner, 1979), since the former are richer in defensive compounds (such as lignin and antiherbivore compounds), which are expensive to synthesize (Mooney & Gulmon, 1979; Chabot & Hicks, 1982). Subsequent studies have supported this hypothesis (Merino, 1987; Diamantoglou et al., 1989; Gower et al., 1989; Damesin et al., 1998) but others have not (Merino et al., 1982; Chapin, 1989; Williams et al., 1989). Several factors could explain the contradictory measures of CC reported in the scientific literature. Firstly, relative estimates of CC will depend on the units with which they are expressed. For example, Sobrado (1991) found that evergreen leaves had higher CC per unit area (g glucose m−2) than deciduous ones. However, recalculation of that data per unit dry mass (g glucose g−1) showed that there were no significant differences in CC between these leaf types. Secondly, the size of the leaf seems to affect leaf CC. For example, Merino (1987) found higher leaf CC in evergreen than in deciduous leaves, but he did not find any difference between these leaf types when species with similar leaf size were compared. Thirdly, comparisons were often made between only two or three species. Moreover, in some cases, the species compared were native to different ecosystem types (tropical, mediterranean, arctic, etc.). Since, differences in resource availability, such as light, nitrogen and phosphorus, appear to affect CC (Griffin, 1994; Poorter, 1994; Griffin et al., 1996; Poorter & Villar, 1997), we may expect ecosystem type to influence CC. Finally, because of the diversity of methods used to calculate CC, a comparison of the available data from different literature sources is unlikely to be a good method to test the hypothesis of whether CC differ among contrasting species and/or between contrasting environments. For example, comparisons of CC values obtained by different methods for the same plant material may differ by as much as 20% (Williams et al., 1987; Griffin, 1994). There is little information available on the differences in CC among species from contrasting ecosystems. A major focus of our study was therefore to assess whether leaf CC differ among species with different leaf life-span, and/or among species from contrasting ecosystems. The aims of this study were to test (1) if species with long leaf life-span have relatively high leaf CC, and (2) if mean leaf CC differs between contrasting ecosystems. The relationships between leaf CC and other leaf traits (size, chemical composition, etc.) were also investigated. Materials and Methods Different leaf traits of 162 wild woody species from 14 contrasting ecosystems (Table 1) were studied. Included in this sample, were published data on seven tropical dry forest species in South America (Sobrado, 1991) and 35 species from two rain forests in Africa (Waterman et al., 1980). Both studies followed the same approach as in the present study. The species were classified according to the mean leaf life-span into the following categories: deciduous (4–8 months), semideciduous (5–12 months) and evergreen (> 12 months). Semideciduous species are those that have a leaf longevity of less than 1 yr, but in contrast to deciduous species, keep leaves throughout the year. Data on leaf life-span were taken from literature and from field observations. Nomenclature of the species agreed with the classification given in taxonomic texts for each region (Thomas, 1961; Branwell & Branwell, 1974; Porsild & Cody, 1980; Benson & Darrow, 1981; Moore, 1983; Valdés et al., 1987; Petrides, 1988). Table 1. Type of the ecosystems studied, latitude and longitude, location and the number of deciduous (Dec), semideciduous (S-Dec) and evergreens species (Ever) considered in each ecosystem. Code of ecosystems used is as in Fig. 2. Data of ecosystem 12 are from Sobrado (1991) and data of ecosystems 13 and 14 from Waterman et al. (1980) Code Ecosystem Latitude and longitude Location Dec S-Dec Ever 1 Tundra 75° N 82° W Devon Island, Canada 1 0 2 2 Desert 28° N 106° W Chihuahua, USA 2 1 3 3 Xeric forest 28° N 17° W Canary Islands, Spain 4 4 6 4 Chaparral 36° N 122° W California, USA 1 2 3 5 Xeric mediterranean forest 37° N 6° W Andalucía, Spain 0 11 9 6 Mesic mediterranean forest 36° N 122° W California, USA 6 0 4 7 Mesic mediterranean forest 37° N 6° W Andalucía, Spain 13 2 9 8 Temperate forest 44° N 80° W Toronto, Canada 4 0 0 9 Warm temperate forest 35° N 80° W North Carolina, USA 7 0 1 10 Austral forest 55° S 70° W Tierra del Fuego, Argentina 2 0 5 11 Lauriphyll forest 28° N 17° W Canary Islands, Spain 1 0 17 12 Tropical dry forest 10° N 67° W Charallave, Venezuela 4 0 3 13 Rain forest 5° N 10° W Douala-Edea Forest, Cameroon 1 0 20 14 Rain forest 0°, 32° W Kibale Forest, Uganda 3 0 11 The sampling was done following the same protocol during summer of 1990 and 1991. For each species, several individuals were sampled, taking branches found in different positions of each individual. All the leaves present in each branch were sampled, excluding those with injuries. Leaf blade area was determined in one subsample either using an image analyser (Skye Instruments, Ltd.) or by making photocopies of leaves with paper of known specific weight and weighting the leaf images. Leaf samples were oven dried at 80°C until constant weight, ground and homogenized for subsequent analysis. Ash concentration was determined gravimetrically after combustion of the sample for 4 h at 500°C. Total organic nitrogen concentration was determined by Kjeldhal analysis. Protein concentration was estimated by multiplying nitrogen concentration by 6.25 (Merino et al., 1984). Heat of combustion was determined with an adiabatic bomb calorimeter (Phillipson Gentry Instruments, Inc., USA) with correction for ignition wire melting (Phillipson, 1964). Lipid concentration was determined in leaves of 43 species, most of them native from xeric and mesic mediterranean forests (Spain), austral forest (Argentina), and chaparral scrub (CA, USA). We also include the data on lipid concentration of seven species from tropical dry forest in Venezuela (Sobrado, 1991). Lipid concentration was obtained gravimetrically from soluble diethylether extracts (Allen, 1974). Leaf CC (g glucose g−1) was calculated using a formula based on the growth efficiency of the leaf tissue, heat of combustion and ash and nitrogen concentration of leaves according to Williams et al. (1987): where Hc is the ash free heat of combustion (kJ g−1), A is the ash concentration (g g−1), k is the oxidation state of the nitrogen source (+5 for nitrate or −3 for ammonium), N is the organic nitrogen concentration (g g−1) and Eg is the growth efficiency. The value used in this study for Eg was 0.89 (Williams et al., 1987). In the calculations, we assumed that the nitrogen source was nitrate for all the species, as it is the principal source of nitrogen that is available to higher plants under most field conditions (Taiz & Zeiger, 1991). However, there is a broad consensus that in some ecosystems, for example tundra, the main nitrogen source is ammonia, although tundra species can also use nitrate (Atkin et al., 1993). So, in the case of tundra species, we also consider ammonia as the nitrogen source for calculation of leaf CC. Heat of combustion, ash, and nitrogen and lipid concentration were measured from two different samples obtained from the homogenized leaves for each species. In cases in which variation was higher than 5%, a triplicate sample was considered. The cost of protein synthesis (g glucose spent in protein synthesis per gram of dry tissue) was calculated by multiplying the protein fraction in the tissue by the specific cost of protein synthesis [2.775 g glucose (g protein)−1] (Poorter, 1994). The percentage of CC dedicated to protein synthesis was calculated as the ratio: (cost of protein synthesis/CC) * 100. Statistical analysis of data Statistics were performed using Statistica (StatSoft, 1996) and SPSS (SPSS, 1999). Differences in leaf traits were analysed with a non-parametric test (Kruskal–Wallis) with leaf life-span or ecosystem as class factor. Comparison of leaf traits between leaves with different life-spans (class factor) were made in two ways: (1) pooling all species from different ecosystems and (2) independently in each ecosystem with two or more species belonging to at least two of the three different leaf life-span classes (deciduous, semideciduous or evergreen). Note that most ecosystems studied did not have species belonging to the three leaf types considered, and also that in some ecosystems the majority of species belongs to only one leaf life-span category (Table 1 and Appendix 1). To detect differences in leaf traits between contrasting ecosystems, a non-parametric test (Kruskal–Wallis) with ecosystem type as class factor was performed. In doing so, the differences in leaf CC between contrasting ecosystems could be affected by the dominant leaf life-span of the species in each ecosystem. Therefore, to check if leaf CC were affected by ecosystem type within each leaf life-span type, we performed a Kruskal–Wallis test (ecosystem type as class factor) on two data sets separately; one for deciduous species and the other for the evergreen ones. In this analysis, only those ecosystems with at least four evergreen species or four deciduous ones were considered. Species with semideciduous leaves were not included in the analysis due to the low numbers of species of this type (i.e. there were only two ecosystems with at least four species). A general linear model was fitted to leaf CC data with ecosystem, leaf life-span and leaf area (log) or SLA as explanatory variables using maximum likelihood methods. Ecosystem and leaf life-span were introduced as factors (14 ecosystems, two classes of leaf life-span: deciduous and evergreen) and leaf area (log) or SLA as covariates. Although leaf CC results from the values of three independent variables (heat of combustion, nitrogen and ash concentration) (Eqn 1), the importance of each one of these in explaining the value of leaf CC was unknown. We explored the sensitivity of leaf CC to changes in each component (Hc, N or ash concentration) keeping the other two components constant (similar approach as Griffin et al., 1996). Mean values of Hc, N and ash concentration obtained from our data set were chosen as constant values, and sensitivities of estimates of CC were calculated on the basis of a change in a variable value of plus or minus two times its standard deviation. We calculated the percentage of change in leaf CC that was caused by increasing each one of the independent variables from x̄− 2*S.D. to x̄+ 2*S.D., maintaining the other two variables constant. All means are presented with ± standard deviation. Results Leaf CC of the 162 species ranged from 1.08 g glucose g−1 (Chaetacme aristata, rain forest, Uganda) to 1.92 g glucose g−1 (Erica scoparia, mesic mediterranean forest, Andalucía, Spain) (see Appendix 1), with the mean leaf CC for all species being 1.52 ± 0.12 g glucose g−1. Causes of variation in leaf CC Both the sensitivity of CC to small changes in variable value and the actual variation in parameter values contribute to the relative importance of each parameter in determining variation in CC. For example, CC was shown to be sensitive to small changes in Hc. However, there was very little variation in this measure between samples (C.V. = 6%), and therefore Hc contributed less than expected to the observed variation in CC. Contrary to this, CC was not very sensitive to changes in ash concentration, but this measure showed considerable variation between samples (C.V. = 50%) and therefore it determined more of the variation in CC than expected on the basis of its sensitivity (Fig. 1a). In any case, the most important parameter was shown to be Hc. The sensitivity analysis of leaf CC showed that increasing Hc from x̄− 2*S.D. to x̄+ 2* S.D. caused an increase in leaf CC of 30%. The increase in ash concentration determined a decrease in leaf CC of 15%, whereas the increase in N showed the lowest effect on leaf CC, increasing about 6% (Fig. 1a). Figure 1Open in figure viewerPowerPoint (a) Sensitivity analysis of leaf construction cost to the increase or decrease in only one component (ash free heat of combustion, Hc; nitrogen, N; or ash concentration) keeping the other two components constant. Mean values of Hc, N and ash concentration of our data set were chosen as constant values and the amount of increase or decrease in the variables to detect its effect on leaf construction cost were ±2*S.D. Relationships between leaf construction cost (g glucose g−1) and (b) ash free heat of combustion (r = +0.92, P < 0.0001), (c) ash concentration (r = −0.62, P < 0.001), and (d) nitrogen concentration of leaves (g g−1) (r = −0.11, P > 0.17). Leaf CC was positively correlated with Hc (r = +0.92, P < 0.0001; Fig. 1b) and negatively correlated with ash concentration (r = −0.62, P < 0.001; Fig. 1c). However, leaf CC was not correlated with N (r = −0.11, P > 0.17; Fig. 1d). Since Hc is the main determinant of the differences in leaf CC, it is worth investigating the parameters related to the variation in Hc. The value of Hc is determined by the chemical composition of the tissue (Williams et al., 1987). We found a positive relationship between lipid concentration and both Hc (r = + 0.61, P < 0.0001) and leaf CC (r = + 0.54, P < 0.05, Fig. 2a). This suggests that lipid concentration could be one of the main factors responsible for the observed differences in leaf CC associated with leaf life-span and ecosystem type. Figure 2Open in figure viewerPowerPoint Relationships between (a) leaf construction cost (g glucose g−1) and lipid concentration (g g−1) (r = +0.54, P < 0.05) and (b) protein concentration (g g−1) and ash concentration (g g−1) (r = +0.38, P < 0.00001). Proteins, which are one of the most expensive compounds to synthesize were positively correlated to minerals (r = +0.38, P < 0.00001, Fig. 2b), which have a null construction cost. Therefore, leaves with higher protein concentration have relatively high concentrations of minerals, which tends to keep CC values close to average CC. Leaf CC between different leaf life-span and ecosystem type Mean leaf CC of deciduous species (1.46 ± 0.12 g glucose g−1) was significantly lower (6%; P < 0.05) than those of semideciduous and evergreen species (1.55 ± 0.10 and 1.55 ± 0.12 g glucose g−1, respectively) (Fig. 3a). There were no differences in leaf CC between semideciduous and evergreen species. Leaves of evergreen and semideciduous species showed a higher heat of combustion, a lower nitrogen and ash concentration and a smaller leaf size than those of deciduous species (P < 0.05, Table 2). Deciduous species also show a significantly higher proportion of the leaf CC dedicated to protein synthesis (26%, P < 0.001) than evergreen and semideciduous species (19.6 and 17.5%, respectively) (Table 2). Figure 3Open in figure viewerPowerPoint (a) Mean leaf construction cost expressed per unit dry mass (g glucose g−1), and (b) per unit area (g glucose m−2), and (c) specific leaf area (SLA, m2 kg−1) in relation to the life span of the leaves (Dec, deciduous; S-Dec, semideciduous; and Ever, evergreen). Box limits correspond to ± SE and bars to ± SD. Different letters mean a significant difference (P < 0.05). Table 2. Mean values (± SD) of ash free heat of combustion (Hc), nitrogen and ash concentration, leaf size and the proportion of construction cost dedicated to protein synthesis (CC proteins, [glucose used in protein synthesis/construction cost]*100) in leaves with different life span (deciduous, semideciduous and evergreen) from the 14 ecosystems considered (Table 1). In brackets, number of species considered. For leaf size the number of species considered were 41,19 and 56 for deciduous, semideciduous and evergreen, respectively. Different letters in one column means a significant difference (P < 0.05) Hc (cal g−1) Nitrogen (mg g−1) Ash (mg g−1) Leaf size (cm2) CC proteins (%) Deciduous (n = 49) 20.40 ± 1.03a 22.04 ± 7.7a 84.3 ± 48.9a 96.9 ± 373.5a 26.2 ± 9.0a Semideciduous (n = 20) 21.32 ± 1.34b 15.65 ± 5.2b 57.9 ± 18.5b 3.0 ± 3.3b 19.6 ± 6.2b Evergreen (n = 93) 21.24 ± 1.41b 17.30 ± 7.4b 59.0 ± 30.3b 16.6 ± 21.08c 16.2 ± 6.2b The analysis of differences in leaf CC between deciduous and evergreen species within each ecosystem shows that only in the case of xeric forest (Canary Islands, Spain) and rain forest (Uganda), were evergreen leaves more costly to construct than deciduous leaves (0.05 < P < 0.10). No differences between CC of evergreen and deciduous leaves were found in the five other ecosystems where evergreen and deciduous were present (Table 1). We found significant differences (P < 0.0001) in leaf CC between ecosystems (Fig. 4a) that were mirrored by significant differences in Hc (P < 0.001). Leaves of tundra species showed the highest CC (1.72 ± 0.11 g g glucose g−1) whereas the lowest leaf CC correspond to species from rain forest (Uganda) 1.40 ± 0.13 g g glucose g−1. When ammonia was assumed to be the principal nitrogen source in tundra species, the mean leaf CC was still higher than in other ecosystems (1.60 ± 0.16 g g glucose g−1). The maximum difference in mean leaf CC between ecosystems was 0.32 g glucose g−1, corresponding to about a 23% difference (0.32/1.40). However, when excluding the tundra species because of their low representation (only three species harvested), the ecosystems with highest leaf CC were xeric mediterranean forest (Andalucía, Spain) (1.58 ± 0.10 g glucose g−1) and chaparral (1.58 ± 0.06 g glucose g−1), and then the difference in mean leaf CC between ecosystems was much lower (13%), but still significant. We found a near significant correlation between mean leaf CC of each ecosystem and latitude (P = 0.06, r = +0.51), but excluding the tundra species there was no significant correlation (P > 0.70). Figure 4Open in figure viewerPowerPoint (a) Mean leaf construction cost expressed per unit dry mass (g glucose g−1), and (b) per unit area (g glucose m−2), and (c) specific leaf area (SLA, m2 kg−1) of the species from 14 contrasting ecosystems. Ecosystem code as in Table 1. Box limits correspond to ± SE and bars to ± SD. No data are available for SLA in ecosystems 13 and 14. Deciduous leaves from different ecosystems did not show differences in CC (P > 0.3; range: 1.40–1.50 g glucose g−1). In contrast, leaf CC of evergreen species were significantly different (P < 0.001) between ecosystems, with the highest values for the species from the xeric forest (Canary Islands, Spain, 1.66 g glucose g−1) and xeric mediterranean forest (Andalucía, Spain, 1.63 g glucose g−1). In these ecosystems the evergreen leaves also showed a higher Hc (P < 0.05) than in the other ecosystems. Leaf CC was negatively correlated with SLA (r = −0.28, P < 0.0001) and with the logarithm of leaf blade area (r =−0.42, P < 0.00001, Fig. 5a). SLA and leaf size showed a positive relationship (r = +0.41, P < 0.00001, Fig. 5d). Figure 5Open in figure viewerPowerPoint Relationships between log leaf area (cm2), and (a) leaf construction cost (g glucose g−1) (r = −0.42, P < 0.00001), and (b) lipid concentration of leaves (g g−1) (r = −0.39, P < 0.01), and (c) ash concentration (g g−1) (r = +0.22, P < 0.05), and (d) specific leaf area (m2 kg−1, SLA) (r = 0.43, P < 0.0001). Taking into account the effect of leaf area when comparing the CC of leaves leaf life-span or ecosystem type were shown to have no significant effect (Table 3). Similar results were obtained when using SLA as covariate. Table 3. Results of two ways ANCOVA of leaf construction cost as dependent variable and leaf life-span (deciduous and evergreen) and ecosystem as main factors. In the analysis, log leaf area is included as covariate Source df Sig. Log leaf area 1 0.000 Leaf life-span 1 0.626 Ecosystem 10 0.133 Leaf life-span * Ecosystem 8 0.094 The logarithm of leaf size was negatively correlated with lipid concentration (r = −0.39, P < 0.01, Fig. 5b) and positively correlated with ash concentration (r = +0.22, P < 0.05, Fig. 5c). Leaf CC per unit area and specific leaf area Leaves with different life-span showed much larger differences in CC when expressed per unit area (CCA) (130, 319, 237 g glucose m−2 for deciduous, semideciduous and evergreen species, respectively, P < 0.00001), than when CC was expressed per unit dry mass basis (Fig. 3a,b). These large differences in leaf CCA (calculated as CC/SLA) were due more to the high differences in SLA (13.8, 5.5, 7.2 m2 kg−1 for deciduous, semideciduous and evergreen species, respectively) (Fig. 3c) than to the differences in leaf CC per unit dry mass (Fig. 3a). Similarly, mean leaf CCA were significantly different (P < 0.0001) between ecosystems with values ranging from 86 g glucose m−2 (warm temperate forest, North Carolina, USA) to 321 g glucose m−2 in the chaparral (California, USA) (Fig. 4b). The differences in leaf CCA between ecosystems were also mainly due to the differences in SLA, which ranged from 20.9 m2 kg−1 in warm temperate forest species (North Carolina, USA) to 5.1–5.6 m2 kg−1 in xeric mediterranean forest species (Andalucía, Spain) and chaparral (California, USA), respectively (Fig. 4c). Discussion Leaf CC between different species Leaf CC of the species studied was in the range published for leaves of woody species from different ecosystems (Miller & Stoner, 1979; Merino et al., 1982; Merino, 1987; Chapin, 1989; Sobrado, 1991). Studying young leaves, some authors (Merino et al., 1984; Sobrado, 1994) obtained higher leaf CC than in our study (about 2.2 g glucose g−1). The data in the present study refer to samples representative of all the leaf ages present in the plant (young, medium-aged and mature leaves). Thus, the results obtained represent a mean value of CC of the leaves of all age classes for each species. Leaf CC showed a wide range between different species from 1.08 to 1.92 g glucose g−1, which represents a 78% difference. Assuming similar differences in roots and stems, it could be significant for the carbon balance of a species, as individuals could grow expending 78% less energy than others; which could result, all things being equal, in higher relative growth rates or more energy allocated to defence and/or reproduction (Poorter & Villar, 1997). Higher leaf CC results from higher Hc and lower ash concentrations (Fig. 1b,c). However, leaf CC is not positively correlated with N (Fig. 1d), perhaps due to the positive correlation between N (or protein concentration) and ash concentration (Fig. 2b). Because ash has a null direct cost (Penning de Vries et al., 1974), a higher ash concentration is related to a lower CC. This explains the negative relationship of CC and ash concentration found in a previous study in tomato cultivars (Gary et al., 1998) and in our study. Hc was positively correlated with lipid concentration, which explains nearly 40% of the variation in Hc. Similarly, Pantis et al. (1987) and Peng et al. (1993) found a positive correlation between lipid concentration and either Hc or CC. Lipids are one of the components with the highest energy content per unit mass and are one of the most expensive compounds to synthesize (3.030 g glucose g−1, Penning de Vries et al., 1974). In contrast, Poorter & Bergkotte (1992) did not find any relationship between lipid concentration and leaf CC in herbaceous species from central Europe, which could result from the low lipid concentration in these species (Poorter & Villar, 1997). Other compounds with high specific cost, such as lignin or phenols, could also explain the higher CC in some species. Leaf CC between species with different leaf life-span In contrast to the large differences in leaf CC between species (78%), the difference in mean leaf CC between leaf life-span types was small (6%, Fig. 3a). Differences in mean relative growth rate between deciduous and evergreen are much higher (98 and 15 mg g −1 d−1, respectively) (Reich, 1998). The small difference observed in leaf CC between species with different leaf life-spans is therefore probably unimportant in determining differences in carbon balance between these groups. Higher leaf CC in evergreen and semideciduous species result from their higher Hc and lower ash concentration (Table 2). The higher values of Hc in evergreens and semideciduous are caused by their higher lipid concentrations and possibly other compounds such as lignin or phenols (Poorter & Villar, 1997). Evergreen and semideciduous species from mediterranean ecosystems usually have a thick cuticle (Lillis, 1