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2 Department of Biology, Box 513, Vassar College, 124 Raymond Avenue, Poughkeepsie, New York 12604-0513 USA; and 4 Department of Biology, Indiana University, Bloomington, Indiana 47405 USA
Received for publication June 22, 1999. Accepted for publication February 29, 2000.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Key Words: Allium vineale • genetic correlations • heritability • life history traits • Liliaceae • multiple reproductive modes • trade-offs
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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; Danthonia spicata, Clay, 1982
; Viola mirabilis, Mattila and Salonen, 1995
), aerial and subterranean seeds (e.g., Amphicarpum purshii, Cheplick and Quinn, 1988
; Amphicarpaea bracteata, Trapp and Hendrix, 1988
; see Cheplick, 1987
, for a review), seeds and ramets (e.g., Tussilago farfara, Ogden, 1974
; Fragaria virginiana, Holler and Abrahamson, 1977
), as well as heteromorphic aerial achenes (e.g., Hypochoeris glabra, Baker and O'Dowd, 1982
; Heterosperma pinnatum, Venable and Burquez, 1989
). Adaptive explanations for the maintenance of this diversity posit trade-offs among alternate components of fitness. For example, some propagule types may be favored in competitive situations near the parent, while others may serve a role in dispersal (Schoen and Lloyd, 1984
; Venable, 1985
). Different advantages may also exist for producing sexual vs. asexual progeny, as sexual progeny may be favored in the presence of pathogens or changing environments, and asexual progeny may be favored in static environments.
In addition, genotypes are known to vary their allocation to different modes of reproduction with environmental change. Allocation to vegetative and sexual reproduction changes with plant density in several species (e.g., Ogden, 1974
; Abrahamson, 1975
; Holler and Abrahamson, 1977
; for a review see Loehle, 1987
). Hypochoeris glabra produces a higher proportion of beaked to unbeaked achenes at lower plant density (Baker and O'Dowd, 1982
). In general, higher light and nutrient levels increase the proportion of chasmogamous to cleistogamous flowers (e.g., Schemske, 1978
; Trapp and Hendrix, 1988
; Le Corff, 1993
; but see Mattila and Salonen, 1995
). In Amphicarpum purshii, aerial reproduction occurs under higher resource availability, while subterranean seeds are produced at all resource levels (Cheplick and Quinn, 1982
). Selection would favor such phenotypic plasticity if different propagule types are favored when environmental conditions change (Schoen and Lloyd, 1984
; Loehle, 1987
).
In order for natural selection to currently operate to maintain these diverse reproductive strategies and phenotypic plasticity in allocation patterns, the variation in reproductive mode must have a genetic basis. In fact, the response of a population depends not only on the availability of genetic variation, but also on the existence of genetic correlations between traits (Reznick, 1985
). In particular, negative genetic correlations between life history traits suggest trade-offs in reproductive strategies (Falconer, 1981
; Stearns, 1992
), as selection for increased allocation to one trait will cause a decrease in allocation to the other.
In general, reproductive traits have lower heritabilities than morphological traits (Mousseau and Roff, 1987
), but significant genetic variation in allocation to different reproductive modes has been demonstrated (e.g., cleistogamy vs. chasmogamy, Clay, 1982
; proportion of achene morphs, Venable and Burquez, 1989
; allocation to aerial seeds, Cheplick and Quinn, 1988
). Negative genetic correlations, which indicate trade-offs among life history traits, have also been detected. For example, Law (1979) found a negative correlation between first- and second-year reproduction in Poa annua, and Campbell (1997)
observed a negative correlation between corolla width, which affects pollen export rates and potentially male fitness, and net female fitness. However, not all species demonstrate trade-offs in life history strategies (see Stearns, 1992
, for a review). For example, Cain et al. (1995)
found no evidence for genetic trade-offs among five reproductive traits in Trifolium repens, and Weis, Hollenbach, and Abrahamson (1987) found only indirect evidence for a trade-off between sexual and asexual reproduction in Solidago altissima. In addition, the presence of trade-offs may be dependent on resource availability, with stronger allocation trade-offs present when nutrients are more limiting (e.g., Reznick, 1985
; Biere, 1995
; Schlichting and Pigliucci, 1998
)
Our study organism, Allium vineale, has three modes of reproduction, each with its own implications for genetic variability, dispersal, dormancy, and probability of successful establishment. Two of the modes are asexual in nature, one being aboveground (bulbils), the other belowground (offsets). Sexually produced aerial seeds are the third type of propagule. Within one population, it is possible to find individuals that are reproducing solely asexually, as well as individuals that are reproducing both sexually and asexually, in varying proportions. To determine whether there is genetic variation in allocation to these three reproductive modes and to test for trade-offs between sexual and asexual reproduction in Allium vineale, we asked the following questions: (1) Do genotypes demonstrate heritable genetic variation in allocation patterns to the three propagule types? (2) Are there negative genetic correlations between these reproductive traits? If so, are they stronger when resources are more limiting? (3) Do plants demonstrate phenotypic plasticity in their resource allocation patterns? Is there genetic variation in plasticity, such that genotypes differ in their allocation to each reproductive mode with changing environmental conditions? If so, how do their allocation patterns change?
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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). Seeds weigh 
1 mg, while bulbils range from 5 to 60 mg (mean mass = 19.8 mg; Ronsheim, 1996
). Bulbils germinate that fall, while seeds require several months of cold, moist stratification. Overall, seeds have lower germination and survivorship rates than bulbils (Ronsheim, 1996
). A third propagule type is produced underground. Offsets are underground asexual propagules analogous to the cloves of domesticated garlic. They are the largest of the propagule types (mean mass = 216.9 mg, ranging from 40 to 600 mg), may be dormant for up to 5 yr (Stritzke and Peters, 1972
), and remain next to the parent plant. In addition to underground offsets, plants produce a new bulb each year. These bulbs do not have the thick protective coat of the offsets and are larger than offsets (mean mass = 2391 mg, ranging from 800 to 5000 mg).
Experimental design
Measurement of heritable variation and genetic correlations within Allium vineale is made difficult by the high phenotypic variation in reproductive modes among individuals. Since a high proportion of individuals produce bulbils but no flowers on their aerial reproductive stalk, and others that do produce flowers have low seed set, measurement of heritability through maternal or paternal contributions would be difficult and not representative of the natural population. Instead, we have measured the broad-sense or clonal heritabilities and correlations by using the aerially produced asexual bulbils to replicate genotypes. This approach has the obvious limitation that we are not able to separate the additive genetic variance components from the dominance, epistatic, or maternal components. Furthermore, in sampling the population we were not able to include individuals that produce inflorescences with flowers and no bulbils (a small minority in this population), which may reduce the genetic variation that we measure. We also purposefully collected bulbils from two groups of individuals: one that produced some flowers and a second that produced only bulbils. This resulted in a higher representation in our study than in the field of individuals that produce both flowers and bulbils in their inflorescence, and may inflate our estimate of genetic variance. While these sampling difficulties reduce the relevance of our measured values of heritabilities and genetic correlations to the population of their origin, these estimates are still valuable to address the issue of the evolutionary potential within Allium populations in general.
In this experiment we determined the reproductive allocation of replicates of 16 different genotypes when grown in two fertilization regimes. Infructescences were collected in September 1993 from 16 different plants at a field site in Durham, North Carolina (for details of the field site, see Fowler, 1978
; Fowler and Antonovics, 1981
). Each of the parents was considered a separate genotype, for a total of 16 genotypes. A range of infructescence phenotypes was included, varying from all bulbils to a combination of flowers and bulbils. Of the plants that produced flowers, flower production ranged from 14.8 to 86.2%. Numbers of flowers and bulbils were recorded for each infructescence. Individual bulbils from each of these genotypes were then weighed, planted in research mix (2:2:2:1 of sand, soil, peat moss and gravel) in 6 x 25 cm pots (Deepots, Stuewe and Sons, Inc., Corvallis, Oregon, USA), and randomized on a greenhouse bench under natural light and cool conditions (4°–21°C) in October 1993. Plants were fertilized either once or twice monthly with 150 mL of 20:20:20 Peter's soluble fertilizer at 300 ppm, creating low- and high-nutrient treatments. As this species grows both along roadsides and in highly fertilized agricultural fields, this range in nutrient availability is not unrealistic. There were five replicates for each of the 16 genotypes in each of the two nutrient treatments, with the exception of one genotype (M) that had ten replicates (Ntotal = 170).
Plants were harvested after their leaves died back during the summer of 1994, and the number of bulbils, flowers, and offsets produced was recorded. Bulb mass, total offset mass, total bulbil mass, and the mass of the flowers were also recorded. Fresh mass was used as these propagules were planted in further experiments.
Data analysis
The propensity of plants to produce an aerial reproductive stalk was analyzed with a loglinear model using the CATMOD procedure of SAS (SAS, 1986
). To increase power for this analysis, genotypes were lumped by flowering type (inflorescences containing bulbils only or a mixture of bulbils and flowers). Only plants that produced an aerial reproductive stalk were included in analyses of patterns of biomass allocation, and their masses were analyzed with multivariate and univariate analysis of variance, using the GLM procedure in SAS (SAS, 1986
). Initial mass of the bulbils before planting was used as a covariate. To be able to generalize over a range of environments, nutrient level was treated as a random effect in both the GLM procedure and in the calculation of heritability. Genotype was also treated as a random effect in the GLM procedure, with the effect of both nutrient level and genotype being tested over the interaction mean square. The interaction effect was tested over the residual error. Proportions were arcsine square-root transformed for normality. All other analyses were conducted using ranked data to improve normality, although analyses using log-transformed data gave very similar results. Post hoc comparisons of least squares means were made using Tukey's criterion to correct for multiple comparisons.
We tested for differences in allocation patterns among genotypes using two-way multivariate analyses of variance with profile contrasts (Repeated Profile option in GLM procedure in SAS; Morrison, 1976
). Profile analysis provides an overall test of whether the slopes of lines connecting the means of each reproductive character differ between genotypes, thereby testing whether the response profiles of different genotypes are parallel (Schlichting, 1986
). Thus a significant interaction of Genotype x Profile would indicate that genotypes differ in their allocation to different reproductive modes. The significance of these interactions was tested using Wilk's Lambda criterion because it is derived from a likelihood ratio approach (SAS, 1986
); however, tests using Pillai's Trace and Hotelling-Lawley Trace gave similar results.
Variance component analyses were used to calculate the clonal heritabilities (Fry, 1992
), averaged over the two environments. For traits that could be measured on the maternal parent in the field, we ran parent–offspring regressions. While this heritability estimate is rough (maternal parents were not grown in the same environment as each other or as their offspring), it does give a second heritability estimate for comparison. Genetic correlations among reproductive traits were calculated as follows: where COVCij is the clonal covariance between traits i and j, and VCi and VCj are the clonal variances for traits i and j. A genetic trade-off was inferred when rG < 0 (Platenkamp and Shaw, 1992
; Cain et al., 1995
). Genetic correlations were determined for each nutrient level separately, as allocation trade-offs may be stronger when nutrients are more limiting (e.g., Biere, 1995
; Schlichting and Pigliucci, 1998
). The Profile x Genotype x Nutrient Level interaction was used to test for plasticity in the overall genetic correlation structure across environments (Morrison, 1976
). In addition, pairwise comparisons of the genetic correlations were made for high- vs. low-nutrient level for each set of reproductive traits. To do this, all correlation coefficients were z-transformed and pairs were tested for homogeneity between nutrient levels (Schlichting, 1989
; Snedecor and Cochran, 1989
; Roche and Fritz, 1997
).
Results from the univariate analysis of variance were used to test for the presence of phenotypic plasticity (Schlichting, 1986
; Scheiner, 1993
; Via, 1993
; Pigliucci, Diiorio, and Schlichting, 1997
). Specifically, a significant effect of Nutrient Level for any of the characters measured would indicate phenotypic plasticity. In addition, a significant Genotype x Nutrient Level interaction would indicate that there is genetic variation for plasticity. We used post hoc comparisons of least squares means using Tukey's criterion to correct for multiple comparisons to determine the pattern of phenotypic plasticity. We tested for plasticity in allocation patterns among genotypes using profile analysis (Morrison, 1976
; Schlichting, 1986
). A significant Genotype x Nutrient Level x Profile interaction would demonstrate the presence of genetic variation in plasticity for the pattern of resource allocation to the three reproductive modes.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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2 = 9.9, df = 1). The genotypes also differed significantly in their probability of producing an aerial reproductive stalk, with 99% of genotypes that have only aerial bulbils and 59% of genotypes that have a bulbil-flower mixture producing a stalk (P < 0.0004, 2 = 12.3, df = 1). The Genotype x Nutrient Level interaction was not significant. Genotypes were strongly different in their allocation to bulb, offset, bulbil, and flower production (MANOVA Genotype effect; F60,45 = 6.353, P < 0.0001; Fig. 1). In fact, univariate analyses indicate significant genotypic variance for all reproductive characters measured (Table 1). These differences in reproductive allocation patterns were highly heritable, with eight out of 12 characters having clonal heritabilities >0.5 (Table 1). In particular, flower production, average bulbil mass, and the proportion of bulbils to flowers produced all had clonal heritabilities over 0.74. Average offset mass, number of bulbils, and allocation to belowground bulbs vs. offsets were the least heritable, being most affected by environmental conditions.
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), the heritability estimates obtained from the variance component analyses and parent–offspring regressions of bulbil and flower traits were similar (Table 1). Specifically, the clonal heritability calculated from a parent–offspring regression for flower number was 0.91 (P < 0.0002, r2 = 0.64, N = 16), compared to 0.79 based on the variance component analysis. The clonal heritability of number of bulbils was 0.258 (P < 0.265, r 2= 0.09, N =16) compared to 0.263, and the clonal heritability of proportion of bulbils to flowers produced was 0.82 (P < 0.0001, r2 = 0.65, N = 16) as compared to the estimate of 0.69 based on the variance component analysis. Genotypes differed in their relative biomass allocation to bulb, offset, bulbil, and flower production (multivariate profile analysis of biomass allocation—Profile x Genotype effect; F45,36 = 6.96, P = 0.0001; see Fig. 1). Genotypes that produced a mixture of flowers and bulbils had different resource allocation patterns than did genotypes that produced only bulbils. While there was significant heritable variation within these groups, the difference between these groups captured the majority of the genotypic variation in the experiment. Genotypes that produce inflorescences with only bulbils produced fewer, smaller offsets (Fig. 2A, B) and fewer, larger bulbils (Fig. 3A, B) than genotypes that produced inflorescences with a mixture of flowers and bulbils. Thus nonflowering genotypes allocated more resources to aerial asexual reproduction relative to underground asexual reproduction than did flowering genotypes (Fig. 4). In addition, nonflowering genotypes allocated more belowground resources to bulb rather than offset production (Fig. 5).
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Phenotypic plasticity was found in seven out of the 12 characters measured (Table 1, significant effect of Nutrient Level). In general, plants produced greater biomass and greater numbers of propagules with increased nutrient availability. In contrast, no phenotypic plasticity was found in the relative allocation of biomass to above- and belowground asexual propagules. Average bulbil size was also relatively unaffected by nutrient availability, with only one genotype (B) producing bulbils that differed in size significantly (Fig. 4). Thus, the increase in total mass of bulbils in the high-nutrient treatment was due primarily to plasticity in the number of bulbils produced, not an increase in the average size of bulbils. This pattern is different from offset production, where the increase in total offset mass with nutrient availability was due to plasticity in both number and size of offsets.
Genetic variation in phenotypic plasticity was found in response to increased nutrient availability (MANOVA Genotype x Nutrient Level effect; F56,352 = 2.263, P < 0.0001). In fact, genetic variation for phenotypic plasticity was found for eight of the 12 traits analyzed using univariate analysis of variance (significant Genotype x Nutrient Level interactions; Table 1). In addition, their allocation of resources to different propagule types also varied with nutrient availability (Profile x Genotype x Nutrient Level effect; F42,270 = 2.49, P = 0.0001; see Fig. 6). While plants tended to produce greater bulb, offset, bulbil, and flower biomass in the high-nutrient treatment, this increase was not significant for all genotypes. Interestingly, most of the significant Genotype x Nutrient Level interactions were due to five of the 16 genotypes, with genotypes A, D, G, K, and M demonstrating greater plasticity in response to variation in nutrient availability.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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; Delesalle and Mazer, 1995
), including the allocation to different reproductive modes (e.g., Clay, 1982
; Cheplick and Quinn, 1988
; Venable and Burquez, 1989
). It is perhaps particularly surprising that A. vineale, a predominantly asexual species, demonstrates substantial genetic variability, although high levels of genetic variation have also been found within populations of other asexual species (e.g., Erigeron annuus, Stratton, 1991
; Taraxacum officinale, Lyman and Ellstrand, 1984
; see Ellstrand and Roose, 1987
, for a review). Understanding the selective forces maintaining these divergent reproductive systems represents a major challenge to evolutionary biology. Most theory on the evolution of reproductive systems relies on trade-offs in allocation to different modes of reproduction (see references in the introduction). In this study, we found direct evidence for these trade-offs in the form of significant negative genetic correlations both between allocation to sexual and asexual reproduction and between modes of asexual reproduction. Such trade-offs prevent individual plants from maximizing their reproduction to both modes simultaneously. As one mode of reproduction will likely have higher fitness than the other in any one environment, maintenance of these divergent reproductive modes likely reflects spatial or temporal heterogeneity in their environment.
In contrast to predictions that trade-offs in resource allocation will be greater when nutrients are limiting (e.g., Reznick, 1985
; Biere, 1995
; Schlichting and Pigliucci, 1998
), only two pairs of traits demonstrated stronger trade-offs (larger negative genetic correlations) when resources were more limited. Both of these pairs involved trade-offs in allocation to different forms of asexual reproduction (numbers and mass of bulbils and offsets). Trade-offs were actually weaker when resources were more limiting for the other negatively correlated traits (bulbil mass with bulb mass, offset mass, and flower mass and number, bulbil number with flower mass). However, based on pairwise tests, only one pair of correlations were significantly different between the two environments. While comparison of individual correlations show little difference in the genetic correlation structure between the two environments, the overall correlation structure between the two environments was shown to be significantly different within the profile analysis (the significant Profile x Genotype x Nutrient Level interaction). Profile analysis provides a more powerful test for detecting overall differences in genetic structure by integrating all of the phenotypic measures into a single test.
Trade-offs between different reproductive modes were consistent in both environments, as both sexual seed production and asexual reproduction through offsets were negatively correlated with asexual bulbil production. The genotypes can generally be grouped into two major resource allocation patterns, with some genotypes allocating resources towards fewer, larger aerial asexual propagules, and other genotypes allocating resources to flowers and belowground asexual offsets. The fact that heritable variation in allocation patterns exists within these groups (and that the genetic correlations are not perfect) suggests that these two reproductive strategies do not result from an inherent constraint in allocation, but rather are themselves an outcome of selection. Understanding the selection pressures on these modes of reproduction is made difficult by the fact that these propagules differ not only in their genetic composition, but in their physiological state as well.
The genetic implications of the reproductive modes are clear. While seeds and bulbils have similar dispersal and dormancy patterns (Ronsheim, 1994
), bulbils are genetically identical to the parent and seeds are genetically variable. While the genetic variability found among seeds might result in greater success in variable environments, there is no evidence for that in this population. In general, seeds suffer higher predation rates, lower germination rates, lower survival rates, show no dormancy in the field, and are dispersed no farther than bulbils (Ronsheim, 1994
). In addition, evidence for facilitation among genetically identical siblings growing together would favor bulbil production (Ronsheim, 1996
), as would the local adaptation found within the scale of seed and bulbil dispersal (Ronsheim, 1997
). Evidence of positive feedback between genotypes through their changes in their soil community (Bever, Westover, and Antonovics, 1997
) would also favor asexual propagules. It remains a possibility that rare events, such as pathogen attack, create strong selection for the sexual mode of reproduction. Such an event would abruptly raise the frequency of the sexual form, after which the asexual form would again increase in frequency. Data do not exist to evaluate whether such oscillations in frequency occur, though the frequency of reproductive types does differ between sites (M. L. Ronsheim, personal observation). However, the strong positive genetic correlation demonstrated here between flower and offset production coupled with selection for offsets could provide a nonadaptive mechanism for the maintenance of sexual reproduction.
Asexual reproduction through bulbils and offsets are not ecologically equivalent. Offsets do not disperse spatially but can remain dormant for up to 5 yr (Stritzke and Peters, 1972
), therefore dispersing in time. In contrast, bulbils do not remain dormant and disperse up to a metre away from the parent (Ronsheim, 1994
). Similar heteromorphic dispersal patterns have been found in other plant species, and a negative correlation between dormancy and dispersal has also been observed in Heterosperma pinnatum (Venable and Burquez, 1990
). This pattern results in one propagule type dispersing through time and one through space (Venable and Lawlor, 1980
). While spatial dispersal reduces the probability of sibling competition, dispersed propagules are more likely to experience heterogeneous environmental conditions. Ronsheim (1997)
found evidence that an intermediate dispersal distance, which corresponds to the dispersal distance of bulbils, is optimal in this population of A. vineale. Growth rates near the parent may be reduced as offsets experience competition with the parent or encounter parental pathogens, though this may be less of a problem after they are dispersed in time. As seen in many amphicarpic plants (see Cheplick, 1987
, for a review), bulbils and offsets also differ in relative size and number produced. Offsets can be an order of magnitude larger than bulbils, though with this increase in average size comes a reduction in total offset number relative to bulbils. The subterranean propagules of many amphicarpic species have higher fitness than their aerial counterparts, as a consequence of both their size and burial underground (Cheplick, 1987
).
Phenotypic plasticity in response to nutrient availability was found for several traits. In general, plants produced more offsets, larger offsets, and/or more bulbils, but average bulbil size was unaffected. However, no phenotypic plasticity was found in the relative allocation to above- vs. belowground asexual reproduction, and only three of the 16 genotypes changed their allocation to aerial sexual vs. asexual reproduction by producing more bulbils. This limited degree of plasticity indicates that most plants are unable to change their allocation patterns between different reproductive modes as nutrient availability increases. It is important to note that there was genetic variation in plasticity (as tested with a Genotype x Nutrient Level interaction for individual traits, and with a Profile x Genotype x Nutrient Level interaction for allocation patterns), with only five genotypes accounting for most of the plastic responses. The other genotypes had very limited plasticity in both number and mass for all the propagule types, with seven genotypes showing no significant plasticity at all, despite a doubling in nutrient availability. Thus there is limited potential for selection to increase the relative allocation of resources to asexual bulbils vs. flowers when more nutrients are available; however, the lack of genetic variation in plasticity for allocation to above- vs. belowground asexual reproduction will constrain selection to act to favor individual genotypes, regardless of nutrient level.
In summary, we demonstrate that the variation in resource allocation to reproductive mode has a genetic basis and that there are clear life history trade-offs between flower and bulbil production, as well as between offset and bulbil production. As the three propagule types vary widely in genetic variability, dispersal, and dormancy, these different allocation patterns are likely to affect plant fitness. In addition, with limited phenotypic plasticity in allocation to aerial asexual vs. sexual reproduction and to above vs. belowground asexual reproduction, allocation patterns are unlikely to change in response to nutrient availability.
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FOOTNOTES |
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2 Author for correspondence (e-mail: maronsheim{at}vassar.edu
).
3 e-mail: jbever{at}bio.indiana.edu
.
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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