META-ANALYSIS OF SOURCES OF VARIATION IN FITNESS COSTS OF PLANT ANTIHERBIVORE DEFENSES

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1 Ecology, 83(1), 2002, pp by the Ecological Society of America META-ANALYSIS OF SOURCES OF VARIATION IN FITNESS COSTS OF PLANT ANTIHERBIVORE DEFENSES JULIA KORICHEVA 1 Section of Ecology, Department of Biology, University of Turku, FIN Turku, Finland Abstract. Plant defense theories predict that allocation to antiherbivore defenses should impose a cost on plants, manifested as a reduction in growth and reproduction. However, the empirical evidence for the existence of such trade-offs is conflicting, suggesting that significant fitness costs of defense arise in some circumstances but not in others. A metaanalysis of 70 studies assessing the relationship between measures of plant defense and growth or reproduction has been conducted to examine the relative importance of several potential sources of variation in the fitness costs of defense. The magnitude of fitness costs varied depending on whether they were measured at the level of phenotype or genotype. The mean magnitude of among-genotype correlations (AGCs) between defense and fitness measures (r 0.30) was higher than that of among-phenotype correlations (APCs; r 0.15). Moreover, AGCs tended to be more negative when defense was assessed as the inverse of herbivore densities or damage rather than in terms of single specific chemical or structural traits. The magnitude of APCs was greatly influenced by environmental variation; phenotypic costs were lowest under controlled experimental conditions and highest in studies that minimized genetic variation among plants. In addition, the magnitude and sign of APCs varied depending on nutrient availability and the type of defensive compound. APCs were negative at high levels of nutrient availability and for defenses associated with alkaloids and phenolics but tended to be positive at low levels of nutrient availability and for defenses associated with terpenoids. In contrast, the magnitude of fitness costs was not significantly affected by the presence of herbivores, type of plant, type of defense (constitutive, mechanical, or induced), concentrations of defensive compounds, or measure of plant fitness. The above patterns of variation in the magnitude of correlations between defense and fitness measures are inconsistent with the notion that fitness costs are incurred through diversion of common limited resources from growth and reproduction to defense (allocation costs). Instead, the prevalence of significant negative correlations under uncontrolled environmental conditions and their persistence in the presence of herbivores both imply that fitness costs of defense may often arise through interactions between plants and their abiotic and biotic environment (competitors, pollinators, different types of herbivores, their natural enemies, and various types of abiotic stresses). Because the above aspects have usually been excluded in studies aiming at detecting internal allocation trade-offs, the failure to detect costs in some cases may be a consequence of the experimental design. Future studies should examine the relative importance of opportunity and ecological types of costs by manipulating various aspects of plant environment. Key words: allocation costs; antiherbivore defense; ecological costs; meta-analysis; opportunity costs; trade-off. INTRODUCTION The assumption that production of antiherbivore defenses is costly and results in trade-offs with plant growth and reproduction forms the cornerstone of most plant defense theories (Feeny 1976, Chew and Rodman 1979, Rhoades 1979, Coley et al. 1985, Gulmon and Mooney 1986, Bazzaz et al. 1987, Herms and Mattson 1992) and is commonly invoked to explain both variation in the expression of constitutive defenses in natural populations (Rausher 1996) and the evolution of inducible defenses (Karban and Myers 1989, Harvell Manuscript received 24 February 2000; revised 1 September 2000; accepted 7 November 2000; final version received 16 January julkoric@utu.fi ). Since the concept of fitness costs is central to plant defense theories, numerous attempts have been undertaken to measure these costs, using a variety of methods (reviewed in Simms 1992, Zangerl and Bazzaz 1992, Bergelson and Purrington 1996). The results of these studies, however, have been inconclusive; significant fitness costs of defenses have been found in some cases (e.g., Berenbaum et al. 1986, Coley 1986, Baldwin et al. 1990, Han and Lincoln 1994), but not in others (e.g., Simms and Rausher 1989, Rousi et al. 1991, 1993, Adler et al. 1995). It has therefore been suggested that future studies should move beyond the simple cataloging of the presence of costs and address the causes of variation in study outcomes (Simms 1992, Bergelson and Purrington 1996). Several explanations have been advanced to account

2 January 2002 FITNESS COSTS OF PLANT DEFENSES 177 TABLE 1. Classification of possible costs of plant antiherbivore defenses. Type of cost Allocation costs (Chew and Rodman 1979, Rhoades 1979, Bazzaz et al. 1987, Simms 1992) Opportunity costs (Coley et al. 1985, Gulmon and Mooney 1986) Ecological costs (Simms 1992, Rausher 1996) Mechanism Trade-offs in the allocation of common limited resources between defense, growth, and reproduction within an individual plant Loss of competitive status as a result of allocation to defense instead of growth early in ontogeny Traits that provide defense against some herbivores may increase susceptibility to other type of herbivores, pathogens, and abiotic stresses, or have deleterious effects on pollinators, predators, and parasitoids Conditions under which cost is most likely to be perceived 1) in the absence of herbivores 2) at low resource availability 3) in slow-growing apparent plants 4) for metabolically expensive defense types 1) in the presence of competitors 2) in fast-growing plants 3) at high resource availability 1) in the presence of various herbivores, pathogens, pollinators, predators, parasitoids, abiotic stresses for the conflicting results of studies assessing fitness costs of antiherbivore defenses. First, the outcome of the study may depend on the method employed to detect a cost. The costs of defense have been measured as either phenotypic or genetic correlations between defense and fitness estimates. Phenotypic correlations determine the pattern of covariation between two traits presented to selection whereas genetic correlations predict how these traits will jointly respond to selection (Stearns 1992). Because phenotypic correlations are the sum of both genetic and environmental components, they may differ in magnitude and sign from their genetic counterparts if the heritabilities of the traits are low and environmental variation is large and has different effects on the phenotype as compared to genetic effects (Pease and Bull 1988, Simms and Rausher 1992). For that reason, negative phenotypic correlations are usually considered as a weaker evidence of fitness costs than genetic correlations (Reznick 1985, Pease and Bull 1988). Reviews by Cheverud (1988) and Roff (1995) have indicated, however, that phenotypic correlations are often suitable substitutes for genetic correlations between various traits in animals (but see Willis et al. 1991). Substitution of genetic correlations by their phenotypic counterparts would be welcome in studies on fitness cost of antiherbivore defenses in plants because phenotypic correlations are much easier to assess as they do not require so large sample sizes and complicated designs as detection of genetic correlations (Simms and Rausher 1992). However, no systematic comparison of reported genetic and phenotypic correlations between plant defense and fitness measures, similar to that undertaken by Cheverud (1988) and Roff (1995), has been attempted so far. Secondly, the magnitude of the fitness costs reported in different studies may vary depending on the measures of plant defense and fitness employed (Berenbaum and Zangerl 1992, Simms 1992). Plant defense is often assessed by measuring the status of a single specific trait (e.g., the concentration of a defensive compound or the density of mechanical structures such as trichomes and spines), and this approach may often underestimate the overall cost of defense, since plant resistance usually involves several interacting mechanisms (Simms 1992). Similarly, plant fitness is seldom assessed directly, as lifetime production of viable seeds, but more commonly estimated by measuring various growth parameters that are correlated with fitness (Silvertown 1982). However, in reproducing plants trade-offs may arise not only between defense and growth, but also between growth and reproduction, and these secondary trade-offs may preclude the detection of fitness costs of defense if plant fitness is measured in terms of growth alone (van Noordwijk and de Jong 1986, Mole 1994). Finally, some of the controversy over the existence of fitness costs of antiherbivore defenses appears to be due to the failure to distinguish between different types of costs (Table 1). Early studies on the fitness costs of defense have mainly considered internal trade-offs within an individual plant in the allocation of common limited resources between defense, growth, and reproduction (Chew and Rodman 1979, Rhoades 1979, Bazzaz et al. 1987). These allocation costs (Simms 1992) include costs of production, transport, storage, and maintenance of defenses (Gershenzon 1994b) that act during the period when defenses are formed and maintained and are predicted to be highest in the absence of herbivores (Simms 1992), under conditions of low resource availability (Rhoades 1979, Zangerl and Bazzaz 1992, Bergelson and Purrington 1996), in slowgrowing apparent plants such as trees (Feeny 1976, Rhoades 1979, Coley et al. 1985), and for metabolically expensive types of defenses (Rhoades 1979, Vrieling and van Wijk 1994). Another type of costs called opportunity costs are incurred through losses of growth and competitive status as a result of allocation to defense instead of growth early in ontogeny (Coley et al. 1985, Gulmon and Mooney 1986). Unlike allocation costs, opportunity costs may be manifested when de-

3 178 JULIA KORICHEVA Ecology, Vol. 83, No. 1 fenses are no longer maintained (e.g., in the case of defenses characteristic of early ontogenetic stages) and are predicted to be higher for fast-growing plants at high resource availability (Coley et al. 1985, Gulmon and Mooney 1986) and in the presence of competitors (Karban and Baldwin 1997, Baldwin and Hamilton 2000). Finally, more recent studies have shown that fitness costs of defense may often be incurred through interactions between plants and their abiotic and biotic environment. For instance, traits that provide defense against some herbivores may increase susceptibility to other types of herbivores, pathogens, and abiotic stresses (Dirzo and Harper 1982, van Dam and Hare 1998, Agrawal et al. 1999), or have deleterious effects on pollinators and herbivore predators and parasitoids (Kauffman and Kennedy 1989, Barbour et al. 1993, Strauss et al. 1999). Such ecological costs (Simms 1992, Rausher 1996) are manifested only in the presence of some additional ecological factor external to the plant. Because most of the studies conducted so far have been designed to measure allocation costs, the failure to find costs in some cases may be a consequence of the experimental design rather than an indication for the lack of trade-offs (Tollrian and Harvell 1999). On the other hand, when costs are detected, they may represent a combination of several cost types. Because different types of costs are manifested under different conditions (Table 1), one way to assess their relative importance is to compare the magnitude of fitness costs in the presence and the absence of herbivores, under low and high resource availability, in fast- and slow-growing plants and for different types of defenses. In the present paper, I examine the above sources of variation in the magnitude of fitness costs by comparing the results of studies assessing the relationship between measures of plant defense and growth or reproduction. While the literature on costs of resistance in plants has been recently reviewed by Herms and Mattson (1992), Simms (1992), Zangerl and Bazzaz (1992), Mole (1994), and Bergelson and Purrington (1996), most of these surveys were narrative and were therefore unable to quantify differences in the magnitude of costs among studies. The only attempt at a quantitative analysis of patterns in the costs of resistance in plants was undertaken by Bergelson and Purrington (1996). The present review, however, differs from that survey both in scope and in the methods employed to combine the evidence across studies. Bergelson and Purrington (1996) included in their analysis only a single category of studies carried out to detect fitness costs: comparisons of fitness of resistant and susceptible genotypes in the absence of herbivores, conducted almost exclusively on annuals and short-lived perennials (crops and weeds). The present analysis complements and extends the review by Bergelson and Purrington, bringing together the evidence for fitness costs of defense from several types of studies (genetic and phenotypic correlations, comparisons of fitness of differentially resistant genotypes and phenotypes, and experimental manipulations of plant defense level) and including various types of plants, from annual herbs to woody evergreens and seaweeds. Moreover, the analysis by Bergelson and Purrington (1996) focussed largely on comparing the frequency of studies showing significant costs of resistance (the prevalence of costs) rather than on the actual magnitude of these costs. Since the probability of obtaining a significant result is a function of both the magnitude of the difference between groups and the sample size (Rosenthal 1994), differences in the number of statistically significant outcomes between two groups of studies could be due either to a biologically important difference in the prevalence of costs or to the differences in sample sizes (Gurevitch et al. 1992). In the present survey, therefore, I compare the magnitudes of costs rather than their statistical significance, using a method of meta-analysis that has been recently introduced into ecology (Gurevitch and Hedges 1993, Arnqvist and Wooster 1995, Osenberg et al. 1999). I restrict the scope of my review to wild plants because fitness costs of antiherbivore defenses in crops could be due to artificial selection for high yield (as in most crops) or for high production of secondary compounds (as in tobacco), and the review by Bergelson and Purrington (1996) have indeed demonstrated that costs of defense were more often found in crops as compared to wild species. MATERIALS AND METHODS The database Relevant studies were identified by examining the reference sections of recent reviews on costs of plant defenses (Herms and Mattson 1992, Simms 1992, Zangerl and Bazzaz 1992, Mole 1994, Bergelson and Purrington 1996) and by conducting key-word searches, using Biological Abstracts and Current Contents computer databases. The search produced 70 studies published during that contained 137 fitness cost estimates for 55 different plant species (see the Supplement). To analyze sources of variation in the magnitude of fitness costs of defenses, I recorded several study characteristics in addition to the estimates of the relationship between defense and fitness measures. These characteristics included presence of herbivores, defense and fitness measures, defense type, and plant type. Herbivores were considered to be always absent in lab studies and always present in field studies unless a special treatment aimed at removing them had been employed and mentioned in the paper. Defense measures were classified as either specific-trait measures (concentrations of defensive compounds or densities of mechanical structures such as trichomes, spines, and thorns) or the inverse of herbivore densities or damage per

4 January 2002 FITNESS COSTS OF PLANT DEFENSES 179 plant (cf. Simms 1992). Fitness measures were classified as either growth estimates (growth rate, biomass, height, radial increment, etc.) or reproduction estimates (number or weight of fruits, seeds, etc.). Defense types were categorized as chemical (assessed in terms of concentrations of various defensive chemicals), mechanical (assessed in terms of density of trichomes, thorns, and spines), or induced (plant resistance experimentally triggered by damage or chemical elicitors). For terrestrial plants, studied species were grouped into four types: annuals, perennial herbs, woody deciduous, and woody evergreen. This grouping reflects the gradient from fast-growing less apparent plants to slowly growing more apparent ones. Due to the small number of studies available, aquatic plants were considered as one group (seaweeds) even though they included both annual and perennial species. From a subset of studies, I was also able to retrieve information on the mean concentrations of the defensive compounds examined and on the level of nutrient availability (low or high) at which the study had been conducted. In sixteen cases, low and high nutrient availability conditions were experimentally created within the same study; in fourteen other studies, nutrient availability was judged as high because plants had been regularly fertilized during the experiment. While the availability of several other resources (e.g., water or light) may limit plant growth, reproduction, and defense allocation, the number of studies manipulating the availability of these resources was too small to allow a separate comparison. The study characteristics used as explanatory variables in the analyses of variation in the magnitude of fitness costs may be not independent from each other, and this may confound the results of analysis. To overcome this problem, I examined the associations between explanatory variables by conducting the chisquare tests of independence (Sokal and Rohlf 1995). If significant association between two variables was revealed, effects of each variable on the magnitude of fitness costs were examined separately at each level of the other variable (cf. Bergelson and Purrington 1996). In many studies more than one estimate was reported concerning the relationship between defense and growth or reproduction measures. Since observations coming from the same study are not independent, the inclusion of several data points from a single study in the analysis may inflate significance levels for statistical tests (Gurevitch et al. 1992). To minimize dependencies in the database, I included several estimates of the relationship between defense and fitness measures from a single study only when they varied with respect to one of the potential sources of variation considered (e.g., defense or fitness measure, defense type, plant type, experimental conditions, or level of nutrient availability). When a single study provided estimates of the relationship between defense and fitness measures from several similar experiments or for several similar estimates of defenses (e.g., concentrations of individual defensive chemicals belonging to the same class of compounds), I included only the results of the experiment which yielded the highest estimate of fitness costs of defense or the combination of variables which exhibited the strongest intercorrelation. This practice provided a more accurate measure of cost because, in many cases, correlation coefficients between defense and fitness measures were reported for significant correlations only whereas for nonsignificant ones even the exact P values were often not available. While this methodology may lead to an overestimation of the absolute magnitude of fitness costs, it should not affect the relative differences in magnitude of costs among different categories of studies, which were the main focus of the present review. Meta-analysis Meta-analysis represents a powerful tool for summarizing the results of studies testing the same hypothesis but differing in experimental design, because it allows the transformation of the outcomes of each study into a common currency, a measure of the effect size, which reflects the magnitude of the effect under study and is independent of sample size. These measures can then be combined across studies to estimate whether the overall effect differs significantly from zero, and can be compared among groups of studies to determine the relative contribution of different factors to the outcome of the study. Meta-analysis has been used to test various ecological hypotheses (e.g., Gurevitch et al. 1992, Koricheva et al. 1998a, b); it is considered to be particularly useful in fields where a moderate to large amount of empirical work is available, the results vary across studies, the expected magnitude of the effect is relatively small, and the sample sizes of individual studies are limited (Arnqvist and Wooster 1995). All these conditions appear to apply to studies on fitness costs of plant antiherbivore defenses. Studies examining fitness costs of antiherbivore defenses in plants could be broadly divided into two categories. In the first category of studies, fitness costs of defenses were assessed by examining the relationship between some measures of defense exhibiting continuous variation and growth or reproduction. The outcomes of such studies are usually in the form of correlation coefficients or regression equations expressing the relationship between plant defense and growth or reproduction measures. In the second category of studies, fitness costs of defenses were quantified by comparing growth or reproduction of two groups of plants exhibiting discrete polymorphism in their resistance to herbivores. This differential resistance may be either constitutive (e.g., cyanogenesis in legumes) or induced by damage or by chemical elicitors. The outcomes of these studies are usually in the form of means and variances of growth or reproduction measures for resistant and susceptible plant phenotypes/genotypes, or

5 180 JULIA KORICHEVA Ecology, Vol. 83, No. 1 t and F values from statistical tests comparing such phenotypes/genotypes. At the first step of meta-analysis, various estimates of fitness costs reported in individual studies were converted into a common measure of association between the measures of plant defense and growth or reproduction, the Pearson product-moment correlation coefficient r. The reasons for choosing r as an effect size estimate were the simplicity of interpretation and the fact that in the majority of studies the results have been reported in the form of correlation coefficients. When the relationship between allocation to growth and defense or reproduction and defense was assessed by regression analysis, values of r were obtained by taking the square root of the coefficient of determination (R 2 ) and attaching the sign of the slope factor. When the original studies reported means and variance of growth or reproduction measures for resistant and susceptible plant phenotypes/genotypes, I first calculated the standardized mean difference statistic Y Y R S d J s where Ȳ R and Ȳ S are the means, s is the pooled standard deviation of fitness measures for the two plant types, and J is a correction term that removes small-samplesize bias (Gurevitch and Hedges 1993), and then transformed d into r (r 2 2 d /(d 4), Rosenthal 1994). The t and F values from statistical tests were converted into r by using formulas r 2 2 t /(t df ) and r F/(F df ) (Rosenthal 1994). Correlation coefficients obtained from individual studies were classified as either among-phenotype correlations (APCs) or among-genotype correlations (AGCs). The first category included both directly estimated phenotypic correlations between defense and fitness measures of individual plants and correlations obtained by the transformation of fitness differences between two differentially resistant phenotypes. Similarly, AGC consisted of directly estimated correlations between defense and fitness measures averaged over genetic families (family-mean correlations sensu Simms and Rausher 1992), and of correlations obtained by the transformation of fitness differences between resistant and susceptible genotypes. When several estimates of genetic correlations have been reported in a single study (e.g., family-mean correlations and genetic correlations estimated from parent offspring regression or sib analysis, Han and Lincoln 1994), only the former measures were used because they were calculated as the Pearson product-moment correlation coefficients, an effect size estimate used in the present meta-analysis. Since the control of plant genetic background has been shown to affect the probability of detecting fitness costs (Bergelson and Purrington 1996), APCs and AGCs were analyzed separately. To examine to what extent environmental variation is confounding genetic variation in phenotypic studies, APCs were further subdivided into three groups: (1) studies providing control for environmental effects (lab or common garden studies conducted under controlled conditions); (2) studies providing control for genetic effects (studies in which genetic variation has been reduced by using only one clone, inbred full-sib seeds from a single plant or seeds resulting from crossing of two plants, e.g., Baldwin et al. 1990, Vrieling and van Wijk 1994); and (3) studies providing no control for either environmental or genetic effects (field studies in which plant individuals of unknown genotype were grown in uncontrolled environmental conditions). Phenotypic correlations reported in the first category of studies were assumed to reflect mainly genetic variation in defense and fitness measures among plants (although genotype environment interactions could have influenced the magnitude of APCs observed in a given environment), phenotypic correlations in studies of the second category should be due to environmental variation, and phenotypic correlations in the third category of studies measure the combined effects of the genotype and the environment. Comparison of phenotypic correlations reported in these three categories of studies should therefore provide some insight into the relative importance of environmental and genetic effects in shaping the magnitude of phenotypic correlations between defense and fitness measures in plants. Estimates of genetic correlations may be inflated to different degree by maternal environment effects, and designs based on clone or maternal family means are considered to be particularly troublesome in this respect (Libby and Jund 1962, Falconer 1989, Simms and Rausher 1992). Therefore, studies reporting AGCs were subdivided into three groups depending on whether the estimates of AGCs were obtained from comparison among paternal half-sib families, maternal halfsib families, or among clones, and the magnitudes of AGCs was compared among these studies as described in the next paragraph. Individual correlation coefficients were z-transformed, weighed by their sample sizes, and combined across studies using the MetaWin 2.0 statistical program (Rosenberg et al. 2000) and the mixed effects model of meta-analysis (Gurevitch and Hedges 1993). The relationship between the measures of plant defense and growth/reproduction was considered significant if the 95% confidence interval of the mean z-transformed correlation coefficient did not include zero. To test the importance of different sources of variation in determining the sign and the magnitude of the correlation between measures of plant defense and growth or reproduction, studies were subdivided on the basis of various study characteristics, and within- and betweengroup heterogeneity was examined using a chi-square test statistic, Q. At the end of the analysis, the mean z values for each group and their 95% confidence inter-

6 January 2002 FITNESS COSTS OF PLANT DEFENSES 181 FIG. 1. Means and 95% confidence intervals for among-phenotype correlations (APCs) and among-genotype correlations (AGCs) between measures of antiherbivore defense and plant fitness: (A) comparison across all studies; (B) comparison restricted to studies in which both types of correlations are estimated. vals were back transformed to a common correlation coefficient for ease of interpretation. Because my analysis was based only on published studies, the results could be flawed if the decision to publish is influenced by the results of the study (e.g., if there is a bias towards publishing only significant negative correlations between plant defense and growth or reproduction measures supporting the concept of fitness costs). To test for the existence of publication bias in the data set, I used the funnel plot technique (Light and Pillemer 1984, Palmer 1999). A funnel plot is a scatterplot of effect size vs. sample size for a group of studies. If no bias is present, this plot should be shaped like a funnel because studies with small sample FIG. 2. Effect size in relation to sample size for amongphenotype and among-genotype correlations between measures of antiherbivore defense and plant fitness. sizes typically display more variation about the true mean effect size than larger studies. In addition, the magnitude of the effect size should be independent of the sample size. RESULTS Both mean APCs and AGCs between defense and fitness measures were negative and significantly different from zero, as indicated by their 95% CI (Fig. 1A). The magnitude of AGCs tended to be larger than that of APCs (Q b 2.81, P 0.09, df 1), and this pattern was not confounded by differences between phenotypic and genetic studies in plant type (woody vs. herbaceous, , df 1, P 0.86), defense measures (specific trait vs. inverse of herbivory, , df 1, P 0.09), or fitness measures (growth vs. reproduction, , df 1, P 0.88). The difference between the two correlation types was even more pronounced when only studies reporting both APCs and AGCs were compared (Fig. 1B; Q b 8.26, P 0.004, df 1). As expected, total heterogeneity among studies was very high (Q t 222.6, P , df 111 for APC, and Q t 41.9, P 0.013, df 24 for AGC), indicating that the studies analyzed did not represent single coherent groups sharing a common effect size. Plotting the values of APCs and AGCs against sample sizes produced a typical funnel plot with greater scatter in studies based on small sample sizes and a lack of significant relationship between magnitude of effect size and sample size (Fig. 2), a pattern consistent with an absence of publication bias. The magnitude of APCs was highest in studies controlling for genetic variation among plants, lowest in studies that provided control for environmental variation, and intermediate in studies providing control for neither genetic nor environmental effects (Fig. 3; Q b 15.8, P , df 2). The magnitude of AGCs, in contrast, was not significantly different among studies using paternal half-sib design, maternal half-sib design and comparison among clones (Fig. 4; Q b 0.74, P 0.69, df 2). Both APCs and AGCs tended to be more negative

7 182 JULIA KORICHEVA Ecology, Vol. 83, No. 1 FIG. 3. Means and 95% confidence intervals for amongphenotype correlations between measures of antiherbivore defense and plant fitness in studies providing different degree of control for environmental and genetic variation. when defense was assessed as the inverse of herbivore densities or feeding damage rather than in terms of a single specific defensive trait (Fig. 5A), although the difference between the two types of studies was close to statistical significance only for AGCs (Q b 3.43, P 0.06, df 1). Nearly all studies assessing defense as the inverse of herbivory were conducted on woody plants (24 out of 25 phenotypic studies and 10 out of 11 genetic studies) whereas, for the specific trait studies, the split between woody and herbaceous plants was more even (33 vs. 30 for APCs and 5 vs. 9 for AGCs, , df 1, P for APCs and , df 1, P for AGCs). To remove the possible bias due to differences in plant type, I repeated the analysis of defense measures for woody plants only. Again, there was a tendency for studies assessing defense as the inverse of herbivory to reveal larger fitness costs than studies measuring individual defensive traits (mean r 0.18 vs. r 0.12 for APCs and r 0.54 vs. r 0.23 for AGCs), but FIG. 4. Means and 95% confidence intervals for amonggenotype correlations between measures of antiherbivore defense and plant fitness as affected by the nature of genetic units compared. FIG. 5. Means and 95% confidence intervals for amongphenotype and among-genotype correlations between measures of antiherbivore defense and plant fitness as affected by (A) defense measure, (B) fitness measure, and (C) presence of herbivores.

8 January 2002 FITNESS COSTS OF PLANT DEFENSES 183 FIG. 6. Means and 95% confidence intervals for among-phenotype correlations between measures of antiherbivore defense and plant fitness at high and low levels of nutrient availability: (A) comparison across all studies; (B) comparison restricted to studies in which both high and low levels of nutrient availability are examined. the difference between the two types of studies was not significant (Q b 0.24, P 0.62, df 1 for APCs and Q b 0.95, P 0.33, df 1 for AGCs). The magnitude of APCs and AGCs did not vary according to whether plant fitness was assessed in terms of growth or reproduction (Fig. 5B; Q b 0.12, P 0.73, df 1 and Q b 0.18, P 0.67, df 1 for APCs and AGCs, respectively). Studies using growth and reproduction as measures of fitness were nonrandomly distributed with respect to plant types: studies measuring growth were mostly conducted on woody plants whereas studies measuring reproduction were more common on herbs ( , df 1, P for phenotypic studies and , df 1, P for genetic studies). However, no significant differences in the magnitude of fitness costs were revealed between the two study types when the comparison of fitness measures was restricted to herbaceous plants only (Q b 1.35, P 0.25, df 1 for APCs and Q b 2.34, P 0.13, df 1 for AGCs; the number of studies measuring reproduction in woody plants was not enough to allow a similar comparison). The magnitude of AGCs and APCs was not significantly affected by the presence of herbivores (Q b 1.98, P 0.16, df 1 for APCs, and Q b 0.64, P 0.42, df 1 for AGCs), although APCs were significant only when herbivores were present (Fig. 5C). Studies excluding herbivores were more often conducted on herbs than on woody plants ( , df 1, P for APCs and , df 1, P for AGCs). However, no significant differences in the magnitude of AGCs and APCs in the absence and presence of herbivores were revealed when the comparison was conducted for herbaceous and woody plants separately (P 0.05). The sign of APCs between defense and fitness measures varied depending on the level of nutrient availability (Q b 5.50, P 0.02, df 1). At high levels of nutrient availability correlations were negative, while at low levels of nutrient availability they tended to be positive (Fig. 6A). The trend remained the same when only studies reporting fitness costs of defense at both high and low levels of nutrient availability were compared (Fig. 6B), although the difference in fitness costs between the two conditions was no longer significant (Q b 1.81, P 0.18, df 1). The number of studies comparing the magnitude of AGCs at different levels of resource availability was not sufficient to allow a similar analysis. Differences among plant types did not explain variation in the magnitude of APCs between defense and fitness measures (Q b 3.79, P 0.44, df 4). Mean APCs were surprisingly similar for all terrestrial plants regardless of their growth form, but tended to be more negative for seaweeds, the only group of aquatic plants examined (Fig. 7A). Due to the smaller number of studies, AGCs could be compared only between woody and herbaceous plants. The difference between the two groups was not significant (Q b 1.69, P 0.19, df 1) although correlations for woody plants tended to be more negative (Fig. 7B). Type of plant was associated with type of defense in phenotypic studies ( , df 2, P 0.001): most of the studies on woody plants examined costs of constitutive chemical defenses (31 out of 38 APCs) whereas studies on herbaceous plants equally often addressed costs of constitutive chemical (13 APCs), constitutive mechanical (17 APCs), and induced defenses (13 APCs). However, comparison of plant types restricted only to studies measuring constitutive chemical defenses did not reveal significant differences among woody plants, herbs and seaweeds in the magnitude of fitness costs (Q b 4.54, P 0.10, df 2). The comparison of fitness costs of different types of antiherbivore defenses could be conducted only for APCs, since the majority of studies assessing AGCs examined the costs of constitutive chemical defenses. The magnitude of APCs was not significantly different for mechanical, chemical, and induced defenses (Fig. 8A; Q b 0.23, P 0.89, df 2). Since in the presence of herbivores all plants may gradually attain an induced status, I repeated the comparison of defense types based only on studies conducted in the absence of herbivores. The difference among groups was not significant (Q b 1.55, P 0.46, df 2), although APCs tended to be more negative for induced defenses (Fig. 8B). Sim-

9 184 JULIA KORICHEVA Ecology, Vol. 83, No. 1 FIG. 7. Means and 95% confidence intervals for (A) among-phenotype and (B) among-genotype correlations between measures of antiherbivore defense and plant fitness as affected by plant type. ilarly, no difference in fitness costs among defense types was revealed when the analysis was restricted to herbs only (Q b 0.06, P 0.97, df 2). For chemical defenses, the sign and the magnitude of APCs varied significantly depending on the type of the defensive compound (Q b 18.21, P , df 2). Production of phenolics and alkaloids was significantly negatively correlated with growth and reproduction measures, whereas concentrations of terpenoids were positively, although not significantly, correlated with plant fitness measures (Fig. 9). Type of the defensive compound was associated with the type of plant ( , df 2, P 0.001): most of the studies on phenolics and all studies on terpenoids were conducted on woody plants whereas all studies on alkaloids were conducted on herbs (mostly on wild species of Nicotiana). Differences in plant type, however, should not confound the comparison of fitness costs associated with different types of defensive compound because, as shown above, the magnitude of fitness costs was independent of the type of plant. The mean concentrations of defensive compounds did not affect the magnitude of APCs, regardless of whether the analysis was conducted for all types of compounds combined or for phenolics only (Fig. 10). The result was the same when the proportion of variance explained by correlations (R 2 ) rather than the absolute values of correlation coefficients was used in the analysis (r 0.25, P 0.20, n 28 for all compounds combined and r 0.28, P 0.28, n 17 for phenolics only). DISCUSSION The major difficulty in evaluating the empirical evidence for the existence of fitness costs of plant antiherbivore defenses lies in the variety of ways that have been used to evaluate these costs (genetic or phenotypic correlations between defense and fitness measures, comparisons of fitness of resistant and susceptible genotypes, experimental manipulations of defense levels, etc.). Previous reviews on the topic attempted to overcome this problem either by evaluating the evidence within each category of studies separately (Simms 1992) or by concentrating on only one type of studies and on statistical significance rather than the magnitude of fitness costs (Bergelson and Purrington 1996). By using meta-analysis, I was able for the first time to combine the evidence for the existence of growth- and reproduction-defense trade-offs provided by different categories of studies, and to examine the relative im- FIG. 8. Means and 95% confidence intervals for among-phenotype correlations between measures of antiherbivore defense and plant fitness as affected by defense type: (A) all studies combined; (B) in the absence of herbivores.

10 January 2002 FITNESS COSTS OF PLANT DEFENSES 185 FIG. 9. Means and 95% confidence intervals for amongphenotype correlations between measures of antiherbivore defense and plant fitness as affected by the type of the defensive compound. portance of various potential sources of variation in shaping the magnitude of fitness costs of defenses. The first factor examined was the difference between methods used to detect fitness costs. Detection of negative genetic correlations is usually considered as a strongest evidence for fitness costs whereas the use of phenotypic correlations as estimates of their genetic counterparts has been repeatedly criticized because the magnitude of phenotypic correlations may be confounded by environmental variation and, therefore, they do not necessarily indicate a genetic basis for a trade-off as required by evolutionary theories (Reznick 1985, Pease and Bull 1988, Willis et al. 1991). Metaanalysis revealed that while both mean APCs and AGCs between defense and fitness measures were negative and significantly different from zero, the magnitude of AGCs was on average much higher than that of APCs. Moreover, the strongest negative APCs were revealed in studies where genetic variation among plants had been minimized, whereas mean APC for experiments conducted under controlled environmental conditions was close to zero. This indicates that the magnitude of phenotypic correlations between defense and fitness measures is indeed greatly influenced by environmental variation. A frequent source of environmental variation that may contribute to the observed difference between the magnitude of APCs and AGCs is variance due to common maternal environment. Such maternal effects tend to increase the apparent amount of genetic variation and may inflate the estimates of genetic correlations based on comparison among maternal families and clones (Libby and Jund 1962, Falconer 1989, Simms and Rausher 1992). Meta-analysis revealed no significant differences in magnitude of AGCs among studies using paternal half-sib, maternal half-sib, and clonal designs. The importance of maternal effects, however, cannot be ruled out because the above comparison was based on few studies and at least in two experiments significant differences in estimates of genetic correlations based on paternal and maternal half-sib designs have been found (Ågren and Schemske 1994, Han and Lincoln 1994). Despite the significance of the environmental component, patterns of variation in phenotypic correlations may still resemble those of genetic correlations if genetic and environmental effects on the developing phenotype are similar (Cheverud 1988). The results of meta-analysis indicated that indeed, despite the difference in magnitude between APCs and AGCs, the patterns of variation in APCs in response to factors examined closely resembled those of AGCs. Both APCs and AGCs tended to be stronger when defense was assessed as the inverse of herbivore densities or damage rather than in terms of single specific chemical or structural traits. This result is understandable, since plant resistance to herbivores is seldom conveyed by a single plant characteristic, but more often involves several mechanisms (e.g., Coley 1983, Matsuki and MacLean 1994, Kause et al. 1999). If some of these traits are omitted from the analysis, the total defensive investments by the plant may be underestimated, resulting in lower or undetectable fitness costs. In addition, the most commonly measured defensive traits (concentrations of defensive metabolites and densities of trichomes or spines) represent ratios with plant biomass or area in the denominator, and are therefore by definition not independent of the growth measures commonly used as estimates of plant fitness (Koricheva 1999). Assessing the level of plant defenses as the inverse of herbivore densities or damage per plant avoids the above shortcomings of the specific trait approach, but may convey a misleading picture when the mechanism of resistance to herbivory involves tolerance or FIG. 10. Among-phenotype correlations between measures of antiherbivore defense and plant fitness in relation to average concentrations of phenolics and other defensive compounds (r 0.26, P 0.32, n 17 for phenolics, and r 0.11, P 0.57, n 28 for all defensive compounds combined).

11 186 JULIA KORICHEVA Ecology, Vol. 83, No. 1 when herbivore population densities vary between localities (Berenbaum and Zangerl 1992). The approach used by Coley and coworkers (Coley 1988, Jing and Coley 1990) seems to be a fair compromise between the two methods: regressing various plant characteristics against herbivory and using the obtained linear combination of parameters as an estimate of defense investments. Most of the studies on fitness costs of antiherbivore defenses conducted so far have aimed at measuring internal allocation costs which arise due to diversion of common limited resources to defense from growth and reproduction. These costs are predicted to be larger in the absence of herbivores, at low resource availability levels, in slow-growing apparent plants, and for metabolically expensive types of defenses (Table 1). None of these predictions was supported by the results of the meta-analysis. First of all, the magnitude of APCs and AGCs was similar both in the absence and the presence of herbivores, indicating that the benefits of defenses in terms of reduced herbivory did not offset fitness costs of defenses. Secondly, negative APCs between defense and fitness measures were detected only at high levels of nutrient availability, whereas at low nutrient availability levels the correlations tended to be positive. This pattern is predicted by the carbon nutrient balance hypothesis for carbon-based defenses such as phenolics and terpenoids, since their production is assumed to be a function of an excess of carbon which accumulates when plant growth is limited by nutrients (Tuomi et al. 1988, Herms and Mattson 1992). However, stronger negative APCs at high levels of nutrient availability were reported also for nitrogen-based defensive compounds such as alkaloids (e.g., Vrieling and van Wijk 1994, van Dam and Baldwin 1998, Baldwin and Hamilton 2000), which by the carbon nutrient hypothesis are predicted to be produced mainly at high nutrient availability (Bryant et al. 1983). The carbonnutrient balance hypothesis thus appears insufficient to explain the pattern of variation in fitness costs of various plant defenses along the gradient of nutrient availability. Another result of the meta-analysis, which appears to contradict predictions concerning patterns of variation in the magnitude of allocation costs, is the lack of differences in fitness costs among different plant types. Fast-growing plants such as annuals and shortlived perennials allocate relatively little resources to antiherbivore defenses, and are therefore assumed to incur lower costs of defense compared to slow-growing apparent plants such as trees (Feeny 1976, Coley et al. 1985, Herms and Mattson 1992). However, while there was a tendency for AGCs to be more negative in woody plants than in herbs, this difference was not significant. The strongest negative APCs between defense and fitness measures were detected in seaweeds, but this could be due to a small number of studies conducted on these plants as compared to terrestrial ones. Furthermore, the meta-analysis revealed no significant differences in fitness costs between different types of defenses. Induced defenses, which are produced only in response to herbivory, are generally believed to evolve as a cost-saving strategy (Karban and Myers 1989, Harvell 1990) and may therefore be expected to impose smaller fitness costs than constitutive defenses. However, costs of induced and constitutive defenses may be similar if constitutive defenses are mainly associated with metabolically cheap defenses whereas inducibility evolved primarily in expensive defenses. In addition, cost-saving represents only one of many possible reasons why induced defenses may be favored or maintained by selection (reviewed in Agrawal and Karban 1999). For instance, another important but less explored potential benefit of induced defenses may be increased spatial and temporal variability in food quality for herbivores (Adler and Karban 1994, Karban et al. 1997). The lack of difference in the fitness costs of induced and constitutive defenses indicated by the present study suggests that such alternative hypotheses for the evolutionary origin and maintenance of induced defenses are worth exploring. Among constitutive defenses, no difference in fitness costs was detected between mechanical and chemical defenses. Skogsmyr and Fagerström (1992) argued that the production of mechanical defenses such as spines and thorns should be more expensive in terms of growth than the majority of chemical defenses, because (1) thorns and spines are not recyclable, and (2) they are constructed of the same material as biomass, and are therefore always limited by the same resources. Another argument for the higher cost of mechanical defenses as compared to chemical defenses was developed by Grubb (1992), who noted that while many chemicals involved in plant resistance have other functions in plants, which may reduce their allocation costs (Simms 1992), mechanical structures such as spines and thorns have evolved primarily as a defense against herbivores. Rousi et al. (1996), however, hypothesized that the costs of surface defenses may have been minimized due to the allometric relationship between surface area and body mass (Schmidt-Nielsen 1984): larger plants have a relatively small surface area as compared to smaller plants, and the relative costs of producing surface defenses per plant should therefore be lower for larger plants than for smaller ones. While this argument was developed to explain the lack of relationship between the number of resin droplets on the bark of birch and seedling growth (Rousi et al. 1991, 1993, 1996), it could probably also be extended to surface mechanical defenses such as thorns, spines and trichomes. In the case of chemical defenses, allocation costs consist of the costs of the biosynthesis, storage, transport, and maintenance of defensive compounds (Ger-