| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Ecology |
Department of Biology, University of Missouri–St. Louis, St. Louis, Missouri 63121 USA
Received for publication February 18, 2005. Accepted for publication June 29, 2005.
ABSTRACT
Ontogenetic changes in architecture, carbohydrate reserves, and resource allocation can constrain the ability of plants to compensate for herbivore damage. To evaluate ontogenetic changes in compensation, saplings and reproductive individuals of the tropical tree Casearia nitida were subjected to three levels of defoliation (0, 25, and 75% leaf area removed) and regrowth was quantified. The impact of defoliation on fruit production was evaluated in reproductive trees. In addition, the influence of defoliation on carbohydrate reserves and on the production of phenolic compounds was assessed. Plants at both stages were able to compensate for 25% leaf area loss, but only saplings were able to compensate at the 75% defoliation level. Negative impacts of defoliation on reproductive trees were also suggested by their tendency to produce fewer fruits when defoliated. The concentration of nonstructural carbohydrates decreased with damage in saplings but not in reproductive trees, suggesting an ontogenetic stage-dependent impact of defoliation on carbohydrate reserves. The concentration of phenolic compounds in leaves decreased with increasing leaf damage in both ontogenetic stages. This suggests a resource based trade-off between defense and compensation. The results from this study suggest that ontogeny needs to be considered when assessing plant responses to herbivore damage.
Key Words: Casearia nitida • Chamela • compensation • defoliation • nonstructural carbohydrates • ontogeny • Salicaceae
There are two recognized mechanisms by which plants can minimize the negative impacts of herbivory: (1) the expression of traits that reduce damage by herbivores (i.e., defense and escape; Dirzo, 1984
) and (2) the expression of tolerance, defined as the ability of plants to maintain fitness through growth and reproduction after experiencing herbivore damage (Belsky, 1986
; Rosenthal and Kotanen, 1994
). As a property of genotypes, tolerance has been defined as the reaction norm of the fitness response of a given genotype to a gradient of herbivore damage (Strauss and Agrawal, 1999
; Stowe et al., 2000
), and is quantified as the slope of this reaction norm (Tiffin and Inouye, 2000
). However, when genotypes are unknown, tolerance is often associated with compensation and quantified as the difference in growth and/or reproduction of damaged plants relative to non-damaged plants (Marquis, 1996
; Strauss and Agrawal, 1999
). Field-based studies of compensation in long-lived perennials (e.g., trees) usually require this latter approach, which was the one used in the current study.
Compensation, defined as the replacement of plant biomass lost to herbivores (McNaughton, 1983
), has been associated with increased photosynthetic rates and mobilization of stored resources from source organs to sinks (e.g., from roots and remaining leaves to new leaves; Chapin and McNaughton, 1989
; Hochwender et al., 2000
). As a consequence, defoliation may significantly decrease stored reserves in plants (Li et al., 2002
). Such responses to damage have been found to be influenced by extrinsic factors, such as nutrient (Chapin and McNaughton, 1989
) and light availability (Anten and Ackerly, 2001
), but also by intrinsic plant attributes. For example, resource allocation to functions other than growth, such as defense or reproduction, may compete for resources and constrain the ability of plants to compensate for tissue lost to herbivores (van der Meijden et al., 1988
; Marquis et al., 1997
; McConnaughay and Coleman, 1999
). Plant sectoriality alone may influence the degree to which resources and hormones can be mobilized from source to sink organs to produce new tissues (Marquis, 1996
), whereas plant architecture, (more broadly defined to include sectoriality as well as plant size and complexity; Lawton, 1983
), determines the number and distribution of meristems that can be activated in response to damage (Rosenthal and Welter, 1995
; Marquis, 1996
).
Plant ontogeny can influence the ability of plants to compensate due to developmental changes in plant architecture, storage capacity, and resource allocation to different functions (e.g., storage, defense, reproduction; Kozlowski, 1971
; Marquis, 1984
; Trumble et al., 1993
; Gedroc et al., 1996
). In the case of woody species, an increase in the plant age is associated with changes in resource allocation patterns, as the carbon/nutrient balance, storage capacity, and access to water and nutrients usually increase, while root to shoot ratio, growth rate, photosynthesis, stomatal conductance, hormone production, and metabolic activity typically decrease (Kozlowski, 1971
; Poethig, 1990
; Bond, 2000
; Farnsworth, 2004
). In addition, morphological differences between juvenile and adult trees include variation in leaf morphology, phyllotaxy, shoot orientation, seasonal leaf retention, presence of adventitious roots, and leaf-specific mass (Poethig, 1990
; Atwell et al., 1999
). Together, these physiological and morphological changes from one ontogenetic stage to another are likely to influence plant responses to herbivore damage, including their use of carbohydrate reserves. In the case of perennial woody species, it has been predicted that the ability to compensate should increase as plants develop, due to resource acquisition and allocation constraints at early stages and to larger storage organs and smaller root to shoot ratio at older stages (Bryant et al., 1991
; Haukioja and Koricheva, 2000
; Stout et al., 2002
; Boege and Marquis, in press
). Nevertheless, there has been relatively little study of the impact of ontogeny on compensation to herbivore damage (but see Brandt and Lamb, 1994
; Tiffin, 2002
; del-Val and Crawley, in press
), particularly for woody species (Seif and Obeid, 1971
; Weltzin et al., 1998
; Haukioja and Koricheva, 2000
; Warner and Cushman, 2002
), and this question has not been experimentally addressed for tropical trees, which are typically under greater herbivore pressure than temperate species (Coley and Aide, 1991
).
Compensatory responses to herbivore damage can influence the expression of plant defense, especially if there is any substrate competition for the synthesis of proteins or carbohydrates used for regrowth and secondary metabolites produced to deter herbivores (Haukioja et al., 1998
). Priority on the expression of compensation over defense or vice versa may be determined by the particular phenology of herbivory and seasonality of a system. If damage is likely to occur in a single pulse during the season, leaves produced after damage would not need to be defended, and compensatory responses should be favored over induction of defenses. By contrast, if herbivore attack occurs intermittently throughout the growing season, production of induced defenses may have priority over compensatory responses in order to avoid further herbivore damage (Karban et al., 1999
). Because a plant's ability to acquire and allocate resources is usually stage-dependent (Tiffin, 2002
), the relative importance of these resource-based trade-offs (e.g., between investment in compensation vs. defense or in induced vs. constitutive defenses) is likely to vary among stages, as dictated by the changing selective pressures and resource demands experienced by plants as they grow and mature.
Study systems in which the dominant herbivores prefer to feed on a particular plant ontogenetic stage are well suited to evaluate ontogenetic differences in the expression of defense and compensation. Such differential herbivore attack has been reported for the tropical deciduous tree Casearia nitida, which receives up to 66% more herbivore damage during the sapling stage than when it reaches its reproductive stage (Boege, 2005
). Because the older stage has been described to be more heavily defended (Boege, 2005
), ontogenetic differences in compensation could also be expected.
The aim of this study was to assess how two ontogenetic stages of a tropical tree respond to damage in terms of regrowth, use and accumulation of stored reserves, and production of defenses. Specifically, the impacts of artificial defoliation were assessed on: (1) subsequent plant growth (i.e., compensation) of two ontogenetic stages of C. nitida, predicting that young saplings would express lower compensation than reproductive trees; (2) fruit production in mature trees, with the expectation that leaf area loss would result in decreased fruit production; (3) mobilization and storage of nonstructural carbohydrates among plant organs of both saplings and reproductive trees, expecting that saplings would have greater constraints to replace carbohydrate reserves (if used to compensate); and (4) the concentration of secondary metabolites in foliage produced after damage, predicting that compensation would constrain the production of defenses if substrate competition occurs between these two functions.
MATERIALS AND METHODS
Study system
This study was carried out in a tropical deciduous forest located within the Estación de Biología Chamela (Universidad Nacional Autónoma de México) in Jalisco, Mexico (19°30'N, 105°03'W). Annual rainfall averages 788 mm, and is concentrated (80%) between July and October (Garcia-Oliva et al., 2002
). Casearia nitida (L.) Jacq. (Salicaceae) (Chase et al., 2002
) is a small deciduous tree (2–6 m tall) common in this forest. Although most of the foliage is produced immediately following the first heavy rains (>10 mm, between June and July), 10–20% of the foliage is produced continuously during the rest of the season (Boege, unpublished data). At the end of the season (October–November), as is typical of most species in this forest, C. nitida drops its leaves. Most herbivore damage occurs during the first 2 months of the rainy season, and mean leaf area loss in C. nitida ranges from 11–23% (Filip et al., 1995
; Boege, 2005
), although 100% defoliation may also occur (K. Boege, personal observations). Flowering of C. nitida occurs during 1 week, about 10 days after the first rain of the season, and fruits require about 2 months to mature (K. Boege, personal observations). Plants were classified as saplings if they were nonreproductive and 0.5–1.5 m tall or as reproductive trees if bearing flowers at the beginning of the rainy season and were 3–4 m tall. These two stages have contrasting architectures (for details, see Boege, 2005
) and presumably different resource allocation constraints related to physiological functions (e.g., growth, reproduction, and storage).
To evaluate the effects of defoliation on subsequent plant growth at different ontogenetic stages, saplings and reproductive trees of C. nitida were artificially defoliated in June of 2002. Forty-five saplings and reproductive trees were located and randomly assigned to one of three defoliation treatments: 0, 25, and 75% of each leaf area removed (N = 15 per treatment and stage). These defoliation levels are within the range of the herbivory typically experienced by C. nitida (K. Boege and R. Marquis, unpublished manuscript). Damage was applied immediately after leaf expansion (but after flowering was completed) at the beginning of the 2002 rainy season, using scissors and simulating natural damage patterns (specifically avoiding midribs, as determined during 2001; K. Boege, personal observations). Additionally, all plants were sprayed every 12 days for the remainder of the season with the nonphytotoxic insecticide, Deltametrin (Agromundo, Mexico City, Mexico) to maintain the treatment damage levels throughout the rainy season. In a separate experiment, Deltametrin did not affect plant growth when compared with control plants sprayed only with water (K. Boege and R. Marquis, unpublished manuscript).
Compensatory growth following leaf damage was measured at the end of the 2002 growing season (November) and at the beginning of the 2003 growing season (July) as new biomass produced (increment in height, twigs, and leaves). At the end of the growing season of 2002, all twigs were counted, and the length (L) of the expansion corresponding to that season was measured on 50 randomly selected twigs per plant. The most distal budscale scar from each twig was easily identified by contrasting differences in color and used as a starting point to quantify twig expansion during the current year. Twig biomass (T) was estimated using the quadratic regression equation: T = 0.003 + 0.008L + 0.0008L2 (R2 = 0.94, P < 0.0001), which was calculated with 150 twigs collected from nonexperimental saplings and reproductive trees. These twigs were measured and dried at 40°C until no changes in mass were detected. Total twig biomass was calculated by multiplying mean twig biomass by the number of twigs on each plant. In 2003, due to time and logistic constraints, a smaller subsample was taken (the upper 10 twigs of each plant) to estimate changes in twig biomass.
Leaves were counted at the end of 2002 and at the beginning of the rainy season in 2003, after the main leaf flush and expansion of the season was completed. In addition, mean leaf area per plant (A) was calculated from leaf width (W) and length (L) of 20 randomly selected leaves per plant, using the equation A = 0.793 + 0.693W x L (R2 = 0.99, P < 0.0001). This regression was obtained from 100 randomly selected and nondamaged leaves collected in 2001 from different saplings and reproductive trees, scanned and measured to nearest 0.01 cm2 with SigmaScan Pro 5.0 (SPSS, 1999
). To estimate total foliage biomass of each plant, the number of leaves was multiplied by the mean leaf area of each plant. To calculate total foliar area per plant in 2002, leaf area remaining after defoliation was added to the leaf area produced during the rest of the growing season.
All three growth variables were ln-transformed to equalize variances and normalize residuals. The impact of defoliation treatment on subsequent growth (compensation) was assessed separately for each year using two-way MANOVA in SAS version 8.00 (SAS Institute, 1999
), with stage and defoliation level considered as class variables and the initial foliage area (ln-transformed) as a covariate, to account for initial differences in plant size and vigor. Subsequent single factor ANOVAs were used to examine which growth variable(s) were most affected by defoliation. In the case of foliage, the amount of biomass replacement required to achieve the observed compensation in 2002 was estimated by calculating the percentage of new leaves produced after defoliation and using ANOVA on ln-transformed values, with the initial foliage area included as a covariate. In addition, a priori orthogonal contrast analyses were defined to (1) detect plant responses to defoliation in terms of foliage replacement (contrast 0 vs. 25 + 75%), predicting that the amount of new biomass would be greater in defoliated plants and (2) to assess if such responses increased with defoliation intensity (contrast 25 vs. 75%), expecting greater biomass production at the highest defoliation intensity, if in fact plants were able to fully compensate. Polynomial contrast analyses designed to detect linear or quadratic responses to defoliation (considering the magnitude of the defoliation treatments; ORPOLY macro, SAS version 8.00) yielded the same conclusions as orthogonal contrast analyses and are therefore not presented here. Fruit production was extremely low during 2002; therefore, the number of developing fruits was counted on reproductive trees only in 2003. The impact of defoliation intensity on fruit production was assessed using a nonparametric Kruskal-Wallis test (Sokal and Rohlf, 1994
), because residuals could not be normalized.
To test if defoliation influenced resource mobilization and rebuilding of carbohydrate reserves, the concentration of nonstructural carbohydrates (NSC) was evaluated in different organs of plants at each ontogenetic stage. At the end of the 2002 growing season, three samples of roots, leaves, and twigs (N = 3 per organ per plant) were randomly collected from five plants of each ontogenetic stage within each defoliation treatment. I deliberately chose to leave two-thirds of the experimental plants nonharvested, in case removal of tissues modified next season's growth and reproduction (which did not occur). Nonstructural carbohydrates were quantified using the phenol–sulphuric method (Dubois et al., 1956
; Marquis et al., 1997
). Samples were oven-dried at 60°C for 48 h and ground to a fine powder (Cyclotec 1093 Sample mill; St. Petersburg, Russia). Soluble sugars were extracted from 15 mg of dry tissue per sample by three washes with 1.5 mL ethanol (80%) at 28°C. Starch was extracted from the remaining pellets, after a 1-h incubation with 4.5 mL of sodium acetate buffer (0.2 M, pH 4.5) in a boiling bath. Extracted starch was then hydrolyzed to glucose with 1 mL of amyloglucosidase (A-7420, Sigma, St. Louis, Missouri, USA), and incubated for at least 8 h at 55°C. Soluble sugars and starch concentrations were detected at 487 nm by spectophotometry (487 nm, Spectronic 501; Milton Roy, Ivyland, Pennsylvania, USA) after a phenol–sulphuric reaction (Dubois et al., 1956
; Ashwell, 1966
; Marquis et al., 1997
). Glucose was used as a standard and treated as described to produce the corresponding standard curves and thereby, results are presented in terms of glucose equivalents. Differences in the percentage of soluble sugars and starch in leaves, twigs, and roots in all treatments and ontogenetic stages were assessed using two-way MANOVAs (SAS Institute, 1999
) on Box-Cox-transformed sugar values and ln-transformed starch values. A priori orthogonal contrast analyses were defined for each plant organ to assess the effects of defoliation on NSC at each ontogenetic stage (0 vs. 25 + 75%), with the expectation that defoliation would trigger the breakdown and mobilization of these stored resources to promote compensation. In addition, plants at each ontogenetic stage under both defoliation treatments were compared (25 vs. 75%) to determine if mobilization of NSC increased and their accumulation decreased with defoliation intensity. The underlying assumption was that plants with greater levels of damage would require more resources to compensate for the loss of tissue than plants at lower damage levels.
Finally, to determine if leaf damage influenced the expression of defensive traits, I quantified total phenolics and condensed tannins in a subset of plants (N = 5 plants/treatment). These metabolites are common defensive compounds in the family Salicaceae (Lindroth and Hwang, 1996
; Glynn et al., 2004
) and in many tropical dry forest species (Janzen and Waterman, 1984
). I used a microscale modification of the Folin-Dennis (Waterman and Mole, 1994
) and proanthocyanidin (Rossiter et al., 1988
) methods to assess total phenolics and condensed tannins, respectively, in one undamaged leaf randomly collected from each plant. Concentrations are expressed in terms of percentage of dry mass purified C. nitida tannin equivalents. Details of these methods are described in Boege (2005)
. Differences in the concentration of each type of compound due to plant ontogeny and defoliation treatment were assessed using two-way ANOVAs on ln-transformed data and the same orthogonal contrast analyses as described. Leaves harvested for chemical analyses had no visual signs of senescence (yellowing, discoloration) and in fact were not shed for at least another month.
RESULTS
Compensatory growth
When all three growth variables were considered, defoliation had a significant effect on plant growth during 2002, but not during 2003. However, such effect was not affected by plant ontogeny (Fig. 1, Table 1). Univariate ANOVA detected a significant effect of defoliation on total foliage produced in 2002 (F1,76 = 10.43, P = 0.0001), and a stage x defoliation effect was detected for foliage replacement (F2,77 = 10.32, P < 0.0001), indicating ontogenetic differences in compensation (Fig. 2). Such differences were confirmed with contrast analyses, which indicated that foliage replacement was greater in defoliated than in nondefoliated saplings (contrast analysis 0 vs. 25 + 75%: F1,78 = 8.54, P = 0.005) and reproductive trees (contrast analysis 0 vs. 25 + 75%: F1,78 = 4.75, P = 0.03). Nevertheless, only saplings showed a graded response to defoliation intensity (contrast analysis 25 vs. 75%: F1,78 = 4.39, P = 0.04), whereas reproductive trees were not able to increase compensation at high levels of damage (contrast analysis 25 vs. 75%: F1,78 = 1.44, P = 0.23; Fig. 2). Defoliation did not have a significant effect on twig biomass and increment in height in 2002 and 2003 (Fig. 1).
|
|
|
2 = 3.54, P = 0.17), due to high within-treatment variation in fruit production.
Nonstructural carbohydrates
Defoliation had significant effects on concentrations of soluble sugars (Table 2; Fig. 3), which decreased in leaves (contrast analysis of 0 vs. 25 + 75%: F1,29 = 6.03, P = 0.02; Fig. 3A) and increased in roots of defoliated saplings (contrast analysis of 0 vs. 25 + 75%: F1,27 = 6.98, P = 0.01; Fig. 3B). In addition, soluble sugars in leaves decreased as damage intensity increased (contrast analysis 25 vs. 75%: F1,29 = 5.89, P = 0.02), while effects of defoliation on soluble sugars in roots were equivalent regardless of defoliation intensity (contrast analysis 25 vs. 75%: F1,27 = 0.01, P = 0.90; Fig. 3). In contrast, defoliation did not affect concentration of soluble sugars in reproductive trees. Marginal effects of defoliation on starch concentration were observed, and it was different between ontogenetic stages (Table 2). Saplings responded to defoliation by reducing starch content in leaves (contrast analysis 0 vs. 25 + 75%: F1,29 = 9.18, P = 0.006; Fig. 3A), and had a tendency to reduce starch content in roots with increasing damage (Fig. 3B). Reproductive plants responded significantly to defoliation intensity only by increasing starch content in twigs (contrast analysis 0 vs. 25 + 75%: F1,28 = 6.57, P = 0.01), and this response was the same in both defoliation intensities (contrast analysis 25 vs. 75%: F1,28 = 2.33, P = 0.14; Fig. 3C).
|
|
|
Plant ontogeny decreased the ability of plants to replace foliage lost at the beginning of the rainy season, in particular when defoliation intensity was high. Negative impact of defoliation at the reproductive stage was also suggested by the tendency of damaged trees to produce fewer fruits. Furthermore, the impact of defoliation on the use and storage of NSCs also differed between ontogenetic stages. Whereas saplings mobilized stored resources to replace lost foliage, reproductive trees did not, or were able to replace such resources during the growing season. Overall, these findings suggest that herbivore damage can have different impacts on plants, depending on the plant's ontogenetic stage.
In 2002, the ability of C. nitida plants to respond to defoliation was similar at both stages when defoliated by 25%, but not at greater damage intensities, given that only saplings responded positively to defoliation intensity with foliage replacement. In contrast, compensatory growth of reproductive trees did not increase at defoliation levels higher than 25% of leaf area lost. These contrasting patterns could be related to constraints imposed by plant sectoriality. Greater plant sectoriality in reproductive trees than in saplings can represent greater constraints in the degree to which resources and hormones move among regions or branches (Honkanen and Haukioja, 1994
; Marquis, 1996
). Furthermore, a lack of compensation at high defoliation intensities in reproductive trees could also be related to resource allocation constraints imposed by other functions such as defense, which is greater in reproductive trees than in saplings (Boege, 2005
), or reproduction (see below). Both architectural and resource allocation constraints are likely to constrain the ability of reproductive trees to mobilize and/or allocate resources to regrowth at high levels of defoliation. Previous studies have found both positive (Warner and Cushman, 2002
) and negative relationships (Seif and Obeid, 1971
; Weltzin et al., 1998
) between compensatory ability and plant age. The latter has been found to occur especially when comparing early ontogenetic stages (i.e., cotyledon stage vs. seedling and saplings stage) or mature trees with senescent trees (Bond, 2000
; Lanner and Connor, 2000
). However, nonlinear relationships between compensation and ontogeny have also been found when comparing more than two stages (del-Val and Crawley, in press
).
Although experiments with artificial defoliation have been heavily criticized because plant responses may be different when damaged by real herbivores (Agrawal, 1998
; Tiffin and Inouye, 2000
), this technique may represent the only viable alternative to impose controlled levels of damage and study compensatory responses in woody trees. Furthermore, an independent study in which herbivore damage was experimentally increased up to 85% in C. nitida plants by excluding insectivorous birds, supports the findings that plants of both stages are able to respond to increased herbivore damage with compensatory growth (K. Boege and R. Marquis, University of Missouri St. Louis, unpublished manuscript). Nevertheless, compensatory responses could be different at earlier stages of C. nitida (e.g., cotyledon stage and seedlings), when stored reserves may be more critical to tolerate herbivory. Thus, further investigation is required to fully understand the influence of ontogeny on the ability of C. nitida plants to compensate. Moreover, although this study showed that plants from both ontogenetic stages were able to compensate after a single moderate (25%) defoliation event, plant responses may be different to multiple defoliation events across years, especially if stored resources are eventually depleted (Parker and Houston, 1971
; Chapin and Slack, 1979
; Cartwright and Kok, 1990
; Houle and Simard, 1996
). In that case, saplings should be affected sooner than reproductive trees, given that they rely on stored resources to compensate, but are unable to fully replace these stores within a growing season.
Defoliation in 2002 did not affect plant growth in 2003; nevertheless, damaged reproductive trees tended to produce at least 23% fewer fruits, although differences were not statistically significant. Defoliation at the beginning of the season may deplete nutrient pools (accumulated in new leaves) and reduce carbon fixation potential. This loss of nutrients could have been a limiting factor for the production of flowers in 2003, despite the lack of an impact of defoliation on leaf area produced. Such impact of defoliation on flower production has been observed in Erythroxylum havanense, a common understory shrub in Chamela forest, in which flower production was affected after being heavily defoliated during the previous season (Domínguez and Dirzo, 1994
). The great variation in fruit production within treatments might have been promoted by factors other than leaf area loss, such as pollinator activity, nutrient and light availability, or by their interaction with compensatory responses of plants (Juenger and Bergelson, 2000
; Sharaf and Price, 2004
).
Defoliation had a significant influence on the mobilization and storage of NSCs in leaves, twigs, and roots, but such influence was stage-dependent. A decrease of starch in leaves and roots of saplings after damage suggests the breakdown of stored resources into simple sugars to be sent to sink organs, such as new leaves, that were intensively produced by defoliated plants. In addition, it also suggests the inability of saplings to accumulate these compounds to rebuild storage reserves. The contrasting impacts of defoliation on soluble sugars, which increased in roots but decreased in leaves of saplings, could be explained by different rates of starch breakdown vs. sugar mobilization, and rebuilding of reserves in these organs. A decrease in starch (Parker and Houston, 1971
; Gregory and Wargo, 1986
; Reich et al., 1993
; Engel et al., 1998
) and an increase in soluble sugars (Parker and Houston, 1971
) as a response to defoliation have been observed in other systems, confirming the important role of mobilization of stored resources for compensation (Li et al., 2002
). In the case of reproductive trees, however, defoliation did not affect concentrations of sugars and starch in roots and leaves, suggesting that NSCs were either not mobilized among these plant organs or were promptly reaccumulated after defoliation. Accumulation of starch in twigs of damaged plants suggests either or both of these possibilities. Increased sectoriality as plants develop could be responsible for the lack of mobilization and accumulation of NSCs (Honkanen and Haukioja, 1994
). If reproductive plants in fact did not mobilize stored resources to replace tissue lost, they might have used current or increased production of photosynthates to compensate for lost tissues (Trumble et al., 1993
).
The negative effects of defoliation on the production of secondary metabolites in new leaves could be due to a lack of inducibility of such compounds in C. nitida, but also due to resource limitation and competition with other functions (Thomson et al., 2003
), such as the observed compensatory responses. A negative relationship between the production of phenolics and re-growth has also been observed in the tree Acacia nigrescens (du Toit et al., 1990
). Resource-based constraints on the simultaneous expression of compensation and defense could be promoted by biochemical trade-offs between the production of proteins and phenolic compounds, because they are both produced through the shikimic acid pathway, and therefore compete for the same biochemical precursor (phenylalanine; Haukioja et al., 1998
). Alternatively, the reduced defense in new leaves of C. nitida could be explained by the fact that, in this site, most herbivore attacks occur at the beginning of the season (Filip et al., 1995
; Boege, 2005
), and as a consequence, compensatory responses should have priority over further production of defenses, due to the low risk of herbivory during the rest of the growing season. Plant ontogeny, however, did not influence the suggested trade-off between compensation and defenses.
The mechanisms by which plants compensate after herbivore damage, and how they change during plant development remain poorly understood. The results of this study suggest that plant ontogeny may affect the degree to which plants compensate after defoliation, and also the physiological responses to herbivore damage (e.g., mobilization and storage of resources). Nevertheless, to better understand how different mechanisms of compensation have evolved and why they change as plants develop, more information is required to identify the environmental, physiological, genetic, and ontogenetic constraints that plants face to maintain fitness through growth and reproduction after sustaining herbivore damage.
FOOTNOTES
1 The author thanks M. Abarca, J. Barruecos, D. Carmona, F. Diaz, L. Duque, C. Espinoza, E. Flores, A. Güemez, A. Martínez, D. Medina, M. Sánchez, O. Sánchez, A. Verduzco, and G. Verduzco for their invaluable help in the field; R. Forkner and R. Marquis for advice with laboratory procedures; R. Marquis, R. Dirzo, and N. Mariano for valuable discussions on the experimental design; and R. Marquis, R. Dirzo, J. Lill, B. Baker, R. Forkner, K. Shultz, P. Van Zandt, E. del Val, A. Gaxiola, T. Knight, D. Ackerly, and two anonymous reviewers for comments that improved the manuscript. Financial support for this research was provided by CONACyT-Mexico, International Centre for Tropical Biology-UM-St. Louis, Organization for Tropical Studies, and by the National Science Foundation-USA (INT-0228229). 
2 (e-mail: kboege{at}servidor.unam.mx
), present address: Department of Biological Sciences, Stanford University, Stanford, California 94305 USA
LITERATURE CITED
Agrawal A. A. 1998 Induced responses to herbivory and increased plant performance. Science 279: 1201-1202
Anten N. P. R. D. D. Ackerly 2001 Canopy-level photosynthetic compensation after defoliation in a tropical understorey palm. Functional Ecology 15: 252-262[CrossRef][ISI]
Ashwell G. 1966 New colorimetric methods of sugar analysis. VII. The phenol-sulphuric acid reaction of carbohydrates. Methods in Enzymology 8: 93-95
Atwell P. E. K. Collin G. N. Turnbull 1999 Plants in action: adaptation in nature, performance in cultivation. Macmillian Education Australia, South Melbourne, Australia
Belsky A. J. 1986 Does herbivory benefit plants? A review of the evidence. The American Naturalist 127: 870-892[CrossRef][ISI]
Boege K. 2005 Herbivore attack in Casearia nitida influenced by plant ontogenetic variation in foliage quality and plant architecture. Oecologia 143: 117-125[CrossRef][ISI][Medline]
Boege K. R. J. Marquis 2005 Facing herbivory as you grow up: the ontogeny of resistance in plants. Trends in Ecology and Evolution 20: 441-448[CrossRef]
Bond B. J. 2000 Age-related changes in photosynthesis of woody plants. Trends in Plant Sciences 5: 349-355
Brandt R. R. Lamb 1994 Importance of tolerance and growth rate in the resistance of oilseed rapes and mustards to flea beetle, Phyllotreta cruciferae (Goez) (Coleoptera: Chrysomelidae). Canadian Journal of Plant Science 74: 169-176[ISI]
Bryant J. P. P. J. Kuropat P. B. Reichardt T. P. Clausen 1991 Controls over the allocation of resources by woody plants to chemical antiherbivore defense. In R. T. Palo and C. T. Robbins [eds.], Defenses against mammalian herbivory, 83–103. CRC Press, Boca Raton, Florida, USA
Cartwright B. L. T. Kok 1990 Feeding by Cassida rubignosa (Coleoptera: Chrysomelidae) and the effects of defoliation on growth of musk thistles. Journal of Entomology Science 25: 538-547
Chapin F. S. I. M. Slack 1979 Effect of defoliation upon root growth, phosphate absorption and respiration in nutrient-limited tundra graminoids. Oecologia 42: 67-79[ISI]
Chapin F. S. I. S. J. McNaughton 1989 Lack of compensatory growth under phosphorus deficiency in grazing-adapted grasses from the Serengueti plains. Oecologia 79: 551-557[CrossRef][ISI]
Chase M. W. S. Zmarzty M. D. Lledó K. J. Wurdack S. M. Swensen M. F. Fay 2002 When in doubt put it in Flacourtiaceae: a molecular phylogenetic analysis based on plastid rbcL DNA sequences. Kew Bulletin 57: 141-181[CrossRef]
Coley P. D. M. T. Aide 1991 Comparison of herbivory and plant defenses in temperate and tropical broad-leaved forests. In P. W. Price, M. Lewinsohn, G. W. Fernandes, and W. W. Benson [eds.], Plant–animal interactions: evolutionary ecology in tropical and temperate regions. Wiley, New York, New York, USA
del-Val E. M. J. Crawley In press Are grazing increaser species better tolerators than decreasers? An experimental assessment of defoliation tolerance in eight British grassland species. Journal of Ecology.
Dirzo R. 1984 Herbivory: a phytocentric overview. In R. Dirzo and J. Sarukhán [eds.], Perspectives on plant ecology, 141–165. Sinauer, Sunderland, Massachusetts, USA
Domínguez C. A. R. Dirzo 1994 Effects of defoliation on Erythroxylum havanense, a tropical proleptic species. Ecology 75: 1896-1902[CrossRef][ISI]
du Toit J. T. J. P. Bryant K. Frisby 1990 Regrowth and palatability of Acacia shoots following pruning by African savanna browsers. Ecology 71: 149-154[CrossRef][ISI]
Dubois M. K. A. Gilles J. K. Hamilton P. A. Rebers F. Smith 1956 Colorimetric method for determination of sugars and related substances. Analytical Chemistry 28: 350-356[CrossRef]
Engel R. K. J. T. Nichols J. L. Dodd J. E. Brumer 1998 Root and shoot responses of sand bluestem to defoliation. Journal of Range Management 51: 42-46
Farnsworth E. 2004 Hormones and shifting ecology throughout plant development. Ecology 85: 5-15[CrossRef][ISI]
Filip V. R. Dirzo J. M. Maass J. Sarukhán 1995 Within- and among-year variation in the levels of herbivory on the foliage from a Mexican tropical deciduous forest. Biotropica 27: 78-86
Garcia-Oliva F. A. Camou J. M. Maass 2002 El clima de la región central de la costa del pacífico mexicano. In A. N. Nogüera Aldrete, J. H. Vega Rivera, A. N. García Aldrete, and M. Quesada Avendaño [eds.], Historia natural de Chamela, 3–10. Instituto de Biología, UNAM, Mexico City, Mexico
Gedroc J. J. K. D. M. McConnaughay J. S. Coleman 1996 Plasticity in root/shoot partitioning: optimal, ontogenetic, or both?. Functional Ecology 10: 44-50[CrossRef][ISI]
Glynn C. A. C. Ronnberg-Wastljung R. Julkunen-Tiitto M. Weih 2004 Willow genotype, but not drought treatment, affects foliar phenolic concentrations and leaf-beetle resistance. Entomologia Experimentalis et Applicata 113: 1-14[CrossRef][ISI]
Gregory R. A. P. M. Wargo 1986 Timing of defoliation and its effect on bud development, starch reserves, and sap sugar concentration in sugar maple. Canadian Journal of Forestry Research 16: 10-17
Haukioja E. J. Koricheva 2000 Tolerance to herbivory in woody vs. herbaceous plants. Evolutionary Ecology 14: 551-562[CrossRef][ISI]
Haukioja E. V. Ossipov J. Koricheva T. Honkanen S. Larsson K. Lempa 1998 Biosynthetic origin of carbon-based secondary compounds: cause of variable responses of woody plants to fertilization?. Chemoecology 8: 133-139[CrossRef]
Hochwender C. G. R. J. Marquis K. A. Stowe 2000 The potential for and constraints on the evolution of compensatory ability in Asclepias syriaca. Oecologia 122: 361-370[CrossRef][ISI]
Honkanen T. E. Haukioja 1994 Why does a branch suffer more after branch-wide than after tree-wide defoliation?. Oikos 71: 441-450[CrossRef][ISI]
Houle G. G. Simard 1996 Additive effects of genotype, nutrient availability and type of tissue damage on the compensatory response of Salix planifolia ssp. planifolia to simulated herbivory. Oecologia 107: 373-378[CrossRef][ISI]
Janzen D. H. P. G. Waterman 1984 A seasonal census of phenolics, fiber and alkaloids in foliage of forest trees in Costa Rica: some factors influencing their distribution and relation to host selection by Sphingidae and Saturniidae. Biological Journal of the Linnean Society of London 21: 439-454[CrossRef]
Juenger T. J. Bergelson 2000 Does early season browsing influence the effect of self-pollination in scarlet glia?. Ecology 81: 41-48[ISI]
Karban R. A. A. Agrawal J. S. Thaler L. S. Adler 1999 Induced plant responses and information content about risk of herbivory. Trends in Ecology and Evolution 14: 443-447
Kozlowski T. T. 1971 Growth and development of trees. Academic Press, New York, New York, USA
Lanner R. M. K. F. Connor 2000 Does bristlecone pine senesce?. Experimental Gerontology 36: 675-685[CrossRef][ISI]
Lawton J. H. 1983 Plant architecture and the diversity of phytophagous insects. Annual Review of Entomology 28: 23-39[CrossRef][ISI]
Li M. H. G. Hoch C. Körner 2002 Source–sink removal affects mobile carbohydrates in Pinus cembra at the Swiss treeline. Trees 16: 331-337[CrossRef]
Lindroth R. L. S. Y. Hwang 1996 Clonal variation of foliar chemistry of quaking aspen (Populus tremuloides Michx). Biochemical Systematics and Ecology 24: 357-364[CrossRef]
Marquis R. J. 1984 Leaf herbivores decrease fitness of a tropical plant. Science 226: 537-539
Marquis R. J. 1996 Plant architecture, sectoriality and plant tolerance to herbivores. Vegetatio 127: 85-97[CrossRef][ISI]
Marquis R. J. E. A. Newell A. C. Villegas 1997 Non-structural carbohydrate accumulation and use in an understorey rain-forest shrub and relevance for the impact of leaf herbivory. Functional Ecology 5: 636-643
McConnaughay K. D. M. J. S. Coleman 1999 Biomass allocation in plants: ontogenetic or optimality? A test along three resource gradients. Ecology 80: 2581-2593[CrossRef][ISI]
McNaughton S. J. 1983 Compensatory plant growth as a response to herbivory. Oikos 40: 329[CrossRef][ISI]
Parker J. S. D. R. Houston 1971 Effects of repeated defoliation on root and root collar extractives of sugar maple trees. Forest Science 17: 91-95
Poethig R. S. 1990 Phase change and the regulation of shoot morphospecies in plants. Science 250: 923-930
Reich P. B. M. B. Walters S. C. Krause D. W. Vanderklein K. F. Raffa T. Tabone 1993 Growth, nutrition and gas exchange of Pinus resinosa following artificial defoliation. Trees 7: 67-77
Rosenthal J. P. P. M. Kotanen 1994 Terrestrial plant tolerance to herbivory. Trends in Ecology and Evolution 9: 145-148[CrossRef]
Rosenthal J. P. S. C. Welter 1995 Tolerance to herbivory by a stemboring caterpillar in architecturally distinct maizes and wild relatives. Oecologia 102: 146-155[CrossRef][ISI]
Rossiter M. C. J. C. Schultz I. T. Baldwin 1988 Relationships among defoliation Q. rubra phenolics and gypsy moth growth and reproduction. Ecology 69: 267-277[CrossRef][ISI]
SAS Institute. 1999 SAS version 8. SAS, Cary, North Carolina, USA
Seif A. M. Obeid 1971 Ecological studies of the vegetation of the Sudan. IV. The effect of simulated grazing on the growth of Acacia senegal (L.) Wild seedlings. Journal of Applied Ecology 8: 211-216[CrossRef][ISI]
Sharaf K. E. M. V. Price 2004 Does pollination limit tolerance to browsing in Ipomopsis aggregata?. Oecologia 138: 396-404[CrossRef][ISI][Medline]
Sokal R. R. F. J. Rohlf 1994 Biometry. Freeman, New York, New York, USA
SPSS. 1999 SigmaScan Pro 5.0 user's guide. SPSS Science, Chicago, Illinois, USA
Stout M. J. W. C. Rice D. R. Ring 2002 The influence of plant age on tolerance of rice to injury by the rice water weevil Lissorhoptrus oryzophylus (Coleoptera: Curculionidae). Bulletin of Entomological Research 92: 177-184[CrossRef][ISI][Medline]
Stowe K. A. R. J. Marquis C. G. Hochwender E. L. Simms 2000 The evolutionary ecology of tolerance to consumer damage. Annual Review of Ecology and Systematics 31: 565-595[CrossRef][ISI]
Strauss Y. S. A. A. Agrawal 1999 The ecology and evolution of plant tolerance to herbivory. Trends in Ecology and Evolution 14: 179-185
Thomson V. P. S. A. Cunningham M. C. Ball A. B. Nicotra 2003 Compensation for herbivory by Cucumis sativus through increased photosynthetic capacity and efficiency. Oecologia 134: 167-175[ISI][Medline]
Tiffin P. 2002 Competition and time of damage affect the pattern of selection acting on plant defense against herbivores. Ecology 83: 1981-1990[ISI]
Tiffin P. B. D. Inouye 2000 Measuring tolerance to herbivory: accuracy and precision of estimates made using natural versus imposed damage. Evolution 54: 1024-1029[ISI][Medline]
Trumble J. T. D. M. Kolodny-Hyrsch I. P. Ting 1993 Plant compensation for arthropod herbivory. Annual Review of Entomology 38: 93-119[ISI]
van der Meijden E. M. Wijm H. J. Verkaar 1988 Defence and regrowth, alternative plant strategies in the struggle against herbivores. Oikos 51: 355-363
Warner P. J. J. H. Cushman 2002 Influence of herbivores on a perennial plant: variation with life history stage and herbivore species. Oecologia 132: 77-85[CrossRef][ISI]
Waterman P. G. S. Mole 1994 Analysis of phenolic plant metabolites. Blackwell Scientific, Oxford, UK
Weltzin J. F. S. R. Archer R. K. Heischmidt 1998 Defoliation and woody plant (Prosopis glandulosai) seedling regeneration: potential vs. realized herbivory tolerance. Plant Ecology 138: 127-135[CrossRef][ISI]
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
