Printer Friendly

Developmental stability in leaves of Clarkia tembloriensis (Onagraceae) as related to population outcrossing rates and heterozygosity.

Developmental stability (Mather 1953; Thoday 1955; or "developmental homeostasis" Lerner 1954) is the capacity to buffer development from small random deviations in the internal and external environments. It can also be thought of as the precision or repeatability of a genetic developmental program. Lack of developmental stability results in low-level within-genotype variation in adult morphology that cannot be attributed to plastic responses to the environment or to programmed developmental changes. Understanding the phenomenon of developmental instability will provide insight into the molecular and developmental regulation of polygenic traits.

The level of developmental stability theoretically can have important consequences for evolution. In general, deviations from the normal morphology of an organism are thought to be maladaptive (Schmalhausen 1949; Thoday 1952, 1958; Dobzhansky and Wallace 1953; Lerner 1954; Waddington 1957; Soule 1982). In animal systems, developmental instability has been linked to disadvantages in mate competition (Moller 1992; Thornhill 1992). Often, developmental instability and decreased fitness are attributed to lower levels of heterozygosity (Mitton and Grant 1984; Palmer and Strobeck 1986). Because selection can affect developmental stability (Mather 1953; Leamy and Atchley 1985), decreased developmental stability might accompany the evolution of new phenotypes (Maynard Smith et al. 1985; Zakharov 1993). Levin (1970a) theorized that developmental instability could expose more variation to the action of natural selection and thereby provide raw material for evolution. Recently evolving phenotypes might therefore display more instability (Levin 1970a; Maynard Smith et al. 1985; Zakharov 1993; but also see Parsons 1993).

For animals, the study of developmental stability has come to be synonymous with the measure of fluctuating asymmetry. Fluctuating asymmetry (FA) is the difference in the value of a trait measured on two sides of a bilaterally symmetric organism (Mather 1953; Van Valen 1962; Soule and Cuzin-Roudy 1982; Palmer and Strobeck 1986). This sort of random variation around a symmetric ideal is usually distinguished from directional asymmetry, in which the trait measured is always bigger on one particular side of the animal than the other, and from antisymmetry, in which one side or the other is always larger (Van Valen 1962).

Animal studies have determined that populations, lines, and families differ in FA (Van Valen 1962; Palmer and Strobeck 1986), that variation in developmental stability has a heritable genetic basis (Mather 1953; Leary et al. 1985); and that selection enhances high or low developmental stability (Mather 1953; Maynard Smith and Sondhi 1960). Experiments designed to test whether level of heterozygosity is directly related to FA in animals have garnered conflicting [TABULAR DATA FOR TABLE 1 OMITTED] results (Mitton and Grant 1984; Palmer and Strobeck 1986; Patterson and Patton 1990; Clarke et al. 1992).

Even though plants offer several advantages over animals in the study of developmental stability, fewer experimental studies have been performed on plants. Variation within clonal genotypes is one measure that has been used to quantify stability in plants (Seburn et al. 1990; Barrett and Harder 1992). In addition, because the plant body consists of repeated nodal units, a variety of within plant measures of variation can be used to estimate stability (Paxman 1956; Roy 1958; Graham et al. 1993). However, care must be taken that the units used to estimate variance are indeed developmentally comparable and not confounded by the effects of programmed developmental changes along the shoot (Paxman 1956) or by environmental changes over time.

Studies using within-plant variance as a measure of stability suggest that variation in developmental stability exists between lines and populations. Paxman (1956) found differences in stability among several lines of tobacco in leaf and flower traits. Levin (1970b) found differences in the stability of flower number per inflorescence in species and hybrids of Liatrus. Several workers have looked at variability in floral organ number as an expression of stability (Roy 1958; Huether 1968, 1969; Ellstrand 1983; Ellstrand and Mitchell 1988) and have found differences between natural populations. Huether (1968) showed that these differences had a genetic basis in Linanthus. Fluctuating asymmetry has been measured in plants using bilaterally symmetric leaves. Studies on tobacco and teak show that levels of FA can differ significantly between different lines (Sakai and Shimamoto 1965; Bagchi et al. 1989).

The earliest studies of developmental instability in plants sought a relationship between instability and increased in-breeding. These studies compared overall variation in pairs of inbred crop lines to their hybrid lines (reviewed in Lerner 1954, and Levin 1970a). Hybrid lines would be expected to show more variation because of their greater allelic diversity and the opportunity for recombination; thus, studies that found greater variation in the parent lines were notable (Johannsen 1907). But the results of these studies are inconsistent (Lerner 1954; Williams 1960; Rowe and Andrew 1964; Levin 1970a). These early lines were often poorly described and not genetically characterized (Johannsen 1907). Chakraborty and Ryman (1983) explain how an inbred line could contain a greater number of distinct genotypes than a heterozygous line and thereby display more variation among individuals. Furthermore, the experiments were conducted in the field, sometimes over several years or locations, and phenotypic plasticity due to environmental effects was rarely factored out as a cause of the variation (a fine exception is Rowe and Andrew 1964). Phenotypic plasticity appears to be unrelated to developmental stability in plants (Bagchi and Iyama 1983) and in animals (Scheiner et al. 1991). The problems of the earliest studies of plant developmental stability can be overcome by measuring variation within individuals rather than within lines (Mather 1953; Thoday 1955; Jinks and Mather 1955; Paxman 1956). However, within-genotype morphological variation has never been used to examine the relationship between heterozygosity and developmental stability in plants.

In this paper, we use three methods to examine developmental stability in four natural populations of Clarkia tembloriensis Vasek in relation to heterozygosity and outcrossing rate. The methods assay within-plant variance in leaf length, variance around a heteroblastic leaf pattern, and FA in leaf characters. The work was conducted in growth chambers to ensure that differences in stability reflect genetic differences between plants. Previous work on C. tembloriensis has shown that differences in levels of heterozygosity between populations are associated with their natural outcrossing rates (Holtsford and Ellstrand 1989) and floral morphology (Holtsford and Ellstrand 1992). Here, we test the hypothesis that because of their lower heterozygosity levels, the selfers should show more developmental instability than the out-crossers.


Seed from four populations of Clarkia tembloriensis, collected in 1986, were provided by T P. Holtsford. These were designated CR, MK, CC1, and I1 (Holtsford and Ellstrand 1989; Table 1). CC1 is a predominantly self-pollinating ([Mathematical Expression Omitted]) population at the northern end of the range, referred to hereafter as NS (northern selfer). I1 is its neighboring out-crossing population ([Mathematical Expression Omitted]) hereafter referred to as NO (northern outcrosser). The mean percentage of heterozygous loci correlates with outcrossing rate in C. tembloriensis; in [Mathematical Expression Omitted], and in [Mathematical Expression Omitted] (Table 1). These two populations are more genetically similar to each other at enzyme encoding loci than either is to any other C. tembloriensis population, (Nei's genetic distance [less than] 0.01; Table 1). At the southern end of the range, CR is a highly selfing population ([Mathematical Expression Omitted], [Mathematical Expression Omitted]) that has as its neighbor the predominantly outcrossing MK ([Mathematical Expression Omitted], [Mathematical Expression Omitted]); these are hereafter referred to as SS (southern selfer) and SO (southern outcrosser), respectively (Table 1). SS and SO are also more closely related to each other than to any other C. tembloriensis populations (Nei's genetic distance = 0.06; Table 1).

Clarkia tembloriensis leaves are simple, lanceolate to elliptic, and have from 0-12 serrations on the margins [ILLUSTRATION FOR FIGURE 1 OMITTED]. The phyllotaxis is basically alternate, but with an early period of opposite leaf arrangement. Flowering occurs only well after the switch to alternate leaf arrangement and is accomplished by a single flower borne per node acropetally, until the plant ceases to produce new leaves. For each plant in the study, a record was made of both the node at which the change in leaf arrangement from opposite to alternate pattern occurred and the node at which the alternate pattern became fixed.

1991 Experiment

For a leaf-growth study, seeds of four randomly chosen maternal plants from each of the four populations were rinsed with 10% Rifampicin (a bactericide) and left under dripping tap water for two nights. The seed was sprinkled on top of wet vermiculite and placed in a 15 [degrees] C growth chamber with 50% relative humidity on 8-h day. An average light intensity of 1200 microeinsteins was maintained. When established, plants were transplanted into 1-gal pots containing two-thirds University of California mix #3 and one-third vermiculite and randomly placed in the same growth chamber with settings of 15 [degrees] C nights and 22 [degrees] C d of 10 h. Plants were watered every other day with Foliage-Pro 9-36 liquid fertilizer (Dyna-Gro Corporation, Novato, CA).

Twenty plants from two to four maternal parents per population were used in the following growth study. Eight plants were from population NS and four were from each of the other three populations. Every other day the length of each leaf on the main axis was measured to the nearest 0.5 mm with a flexible plastic ruler. The plastochron, which is the time between initiation of successive leaf primordia, can be calculated from the resulting growth curves. The distance between curves at the reference point (here when leaf length = 15 mm and leaves are still in their exponential phase of growth) represents the plastochron. To calculate the plastochron, leaf-growth curves must be linear, parallel, and equally spaced at the reference length (Erickson and Michelini 1957). These C. tembloriensis plants met the necessary criteria only at nodes 7-10. Within-plant variance in leaf length over these nodes was compared between populations using the Wilcoxon rank sum test (SAS 1985).

1992 Experiment

For the regression of leaf length on node and the estimation of FA, a larger experiment was performed. Seeds of 10 randomly chosen maternal plants from each of the four populations were treated as above except that growth-chamber settings were changed slightly to improve germination rates and accelerate the plant life cycle. Germination conditions were 8 [degrees] C nights and 21 [degrees] C days of 14 h at 90% relative humidity (RH). After transplanting, pots were placed in three randomized blocks each containing one offspring from each of the 40 maternal parents. Growth conditions were 20 [degrees] C nights at 60% RH and 30 [degrees] C days of 14 h at 50% RH. Plants were watered every 3-4 days with a nutrient solution. Because of early mortality from a root fungus that killed 10% of the plants from the southern populations (SS and SO) and 25% of the plants from the northern populations (NS and No), blocks were incompletely replicated. Population SS was represented by two to three offspring of each of ten maternal genotypes (29 plants in all), NS by one to three offspring of each of nine maternal genotypes (18 plants total), and SO and NO by one to three offspring of each of eight maternal genotypes (24 and 15 plants).

For plants from the southern populations, every leaf from the main axis was collected as it began to yellow and abscised easily. These leaves were fixed in 70% ethanol, acetic acid, and 37% formaldehyde (90:5:5 v/v/v). Some leaves dropped and were lost before they could be collected and fixed. From the northern populations, only leaves from the first five nodes were collected.

Leaf length was measured to the nearest 0.5 mm on a flexible plastic ruler. Leaf traits for the calculation of FA are similar to those used in previous studies (Sakai and Shimamoto 1965; Bagchi et al. 1989). The following traits were measured to the nearest 10th of a millimeter under a dissecting microscope with a stage micrometer: the width on each side of the 1 [degrees] vein (midrib) at the widest point (W1), the width on each side of the midrib at the level of insertion of the uppermost 2 [degrees] vein (W2), the distance between the second- and third-most basal 2 [degrees] veins on each side of the leaf (V1), and the distance between the uppermost two 2 [degrees] veins on each side (V2) [ILLUSTRATION FOR FIGURE 1 OMITTED]. Fluctuating asymmetry (FA) measurements were taken at nodes 1, 2, 3, 7, and 15 in the southern populations, and at nodes 2 and 3 in the northern populations. For the southern populations, a total of 419 leaves were measured on 53 plants. In the northern populations, 123 leaves were measured from 33 plants. To estimate measurement error, traits were measured twice on a subset of the leaves. Measurement error for each leaf trait was calculated to be 1-3% of average trait size and 12-20% of FA.

For the purposes of this study, right was taken to be the side of the leaf that was on the right when it was placed abaxial side up on the dissecting stage (as in [ILLUSTRATION FOR FIGURE 1 OMITTED]). Fluctuating asymmetry was calculated within leaves and, for those leaves at nodes near the base of the plant where leaves are borne opposite each other in pairs, the same data were used to estimate between-leaf FA. Fluctuating asymmetry values calculated between opposite leaves are designated SW 1, SV 1, SW2, and SV2.

Fluctuating asymmetry was taken as the absolute value of right minus left (R - L) after a transformation to account for size; this is equivalent to index #2 of Palmer and Strobeck (1986). Raw R-L scores were positively correlated with total trait size, so R and L were each first divided by a size factor (R + L/2) as recommended by Palmer and Strobeck (1992). Data were further transformed to achieve normality of residuals during analysis of variance using a square-root transformation.

Fluctuating asymmetry data were analyzed by multivariate analysis of variance (MANOVA) using SAS general linear models procedure (SAS 1985); this is equivalent to Levene's Test (Palmer and Strobeck 1986, 1992). Main effects were block, population, maternal family (within population), and node. Maternal family (within population) was designated a random effect. All interaction terms could not be included in the model because blocks were incompletely replicated; interactions involving maternal family were left out. Fluctuating-asymmetry differences between populations were analyzed in separate MANOVAs for northern and southern pairs because different numbers of nodes were sampled from each. Between-population comparisons of FA traits within leaves and between opposite leaves were analyzed separately for northern and southern pairs for the same reason. When Pillai's trace, the test statistic for the MANOVA, indicated significant differences, the first total canonical structure coefficients from a canonical discriminant analysis were consulted to identify traits contributing to the differences between populations (SAS 1985). These coefficients equal the correlation between an individual's value for a dependent variable and the discriminant function score for that individual. They evaluate the contribution of the dependent variable to the significant differences among populations revealed by MANOVA. Partial correlation coefficients for all trait combinations were also obtained from the MANOVA procedure (SAS 1985).

Linear regression of leaf length on node and calculation of [R.sup.2] and mean square error (MSE) for each plant were performed on SAS (SAS 1985). Variances, [R.sup.2], and MSE were compared using the Wilcoxon rank sum test (SAS 1985).


Selfing populations have significantly higher variance in leaf length overall for both year's experiments (NS vs. NO in 1991, P [less than] 0.001; SS vs. SO in 1991, P = 0.058; NO vs. NS in 1992, P [less than] 0.05, and SS vs. SO in 1992, P = 0.0115, sign test, Conover 1980). However, precise patterns changed from year to year. In the northern populations in 1991 [ILLUSTRATION FOR FIGURE 2A OMITTED], selfing plants had higher variances at nodes 1-3 and at nodes above 20. In 1992 [ILLUSTRATION FOR FIGURE 2C OMITTED], for the same populations, selfers had higher variances at all nodes except nodes 3-5. In the southern populations in 1991 [ILLUSTRATION FOR FIGURE 2B OMITTED], selfing plants had higher variances at nodes 1-3 and at nodes above 25. In 1992 [ILLUSTRATION FOR FIGURE 2D OMITTED], for the same populations, selfers had higher variances at nodes 7-22.

1991 Experiment

Data from the leaf-growth study were used to plot the natural logarithm of mean leaf length vs. time [ILLUSTRATION FOR FIGURE 3 OMITTED]. Each curve illustrates leaf growth at a particular node. Note that at the first seven nodes, leaves are born in pairs, an opposite leaf arrangement. At the first three nodes, leaves are truly opposite each other; at nodes 4-6, they are in transition to an alternate arrangement, which is established by node 7. A slight tendency for plants to continue producing successive leaves in pairs is manifested as occasional shorter internodes and plastochron. This pattern, including the exact number of the nodes where the switch to alternate leaf arrangement begins and ends, is remarkably consistent from plant to plant.

Leaves at a set of successive nodes within a plant that reach the same final length and have similar growth rates are developmentally comparable. Within-plant variance calculated over these nodes can be used as a measure of developmental stability. Within each population, leaves at nodes 8-11 look like replicates, reach the same final length [83 [+ or -] 7.5 (SD) mm in the outcrossers, 82.5 [+ or -] 11.5 (SD) mm in the selfers], and have the same growth rate [4.9 [+ or -] 0.38 (SD) mm/d outcrossers, 5.3 [+ or -] 0.65 (SD) mm/d selfers], and thus are developmentally comparable. These nodes lie between the establishment of alternate leaf arrangement and the onset of flowering (which commenced at node 11 in the selfers and at node 16 in the outcrossers). Within-plant variance over nodes 8-11 averaged twice as much [19.78 [+ or -] 15.61 (SD), n = 12] in the selfers as in the outcrossers [11.97 [+ or -] 8.7 (SD), n = 8] but was not significantly different [P = 0.56, Wilcoxon rank sum test; SAS (1985)]. Plastochrons calculated over nodes 7-10 had similar values in selfing [22.3 [+ or -] 13 (SD) hours (n = 12)] and outcrossing [20.4 [+ or -] 15 (SD) hours (n = 8)] plants.

1992 Experiment

Average leaf length changes predictably with position on the plant [ILLUSTRATION FOR FIGURE 4 OMITTED]. At the upper nodes of the plant, leaf length declines linearly with increasing node; the slope is significantly different from zero in all populations, and plots of studentized residuals show a random distribution. The fit to a regression of leaf length on node at these upper nodes of the plants indicates developmental stability (Paxman 1956; Freeman et al. 1993). Progressive changes in leaf size and shape (heteroblasty) are often associated with the onset of flowering (Williams 1965); thus, nodes 25-40 (beyond the first flowering node) were used in the linear-regression comparisons. For selfing plants, [R.sup.2] averaged 0.48 [+ or -] 0.37 (SD), and the true variance around the regression (Steel and Torrie 1980) or mean square error (MSE) averaged 8.39 [+ or -] 9.98. For plants from outcrossing populations, [R.sup.2] was 0.64 [+ or -] 0.34, and MSE was 5.7 [+ or -] 7.30. The variance around the regression lines tended to be larger for selfing plants than for outcrossing plants but these differences were not significant [for [R.sup.2] P = 0.07, for MSE P = 0.15, one-tailed Wilcoxon rank sum test (SAS 1985)].

Fluctuating Asymmetry

Frequency plots of raw R-L values for each trait at each node in each population were examined for evidence of directional asymmetry or antisymmetry (Van Valen 1962). If the leaves displayed directional asymmetry, these plots would have a mean significantly different from zero. If they were antisymmetric, the plots would be bimodal or platykurtic (Van Valen 1962; Palmer and Strobeck 1986). The frequency plots tended to be normal (63 of 96 plots) with a mean of zero (86 of 96 plots). Of the nonnormal plots, most were skewed due to the effects of outliers; thus, their nonnormality can be attributed to type-I error (Sokal and Rohlf 1981) and small sample size. There was no evidence of directional asymmetry or antisymmetry.

Population SS has significantly higher FA than population SO (Table 2). Examining the total canonical structure coefficients (Table 3) shows that this difference is due primarily to differences in four traits, W1, V1, V2, and SV2, that had higher FA in the selfing population. The northern populations did not differ significantly in FA (Table 2).

Least-squares means of each trait for each population are given in Table 4. Least-square means are estimated by holding the values for other components in the model at their means, as a correction for sampling error (Steel and Torrie 1980; SAS 1985). Upper vein distances (V2 and SV2) are consistently more asymmetric than lower vein distances (V1 and SV1).

Multivariate analysis of variance (MANOVA) was also used to test for node effects, which were significant in both pairs of populations (Table 2). In population NS, trait SW2 had greater FA at node 2 than at node 3 (Tables 1-2). In the southern populations, nodes 7 and 15 generally tended to have higher FA values than nodes 1, 2, and 3 (Table 5). For example, the FA for trait V2 was greater at nodes 7 and 15 than at the other nodes measured (1, 2, and 3) (Tables 1, 5).

For trait W1, FA was greater at nodes 1, 7, and 15 than at nodes 2 and 3 (Tables 1, 5). Fluctuating asymmetry of trait SV1 was higher at node 1 than at nodes 2 and 3 (Tables 1, 5). Finally, in population SO, FA of trait V1 was higher at nodes 7 and 15 than at the other nodes measured.

Examination of the univariate analyses showed the block and maternal family (within population) effects were sometimes significant (Table 6). For northern populations, some of the interaction terms were occasionally significant as well. For traits V2 and SW1, the population by block by node interaction term was significant (Table 6), probably because differences in these traits occur between nodes in population NO but not in NS (Table 5). Likewise, for trait SW2, significant interactions occur between block, and node, and between population, block and node (Table 6), that can be attributed to differences between nodes in population NS but not NO.

High FA in one leaf trait does not correlate with high FA in other leaf traits. None of the 24 correlations between trait FAs were significant (at the Bonferroni test criteria of P [less than] 0.002). However, population means for FA values are correlated across traits [Kendall's W = 0.75, P [less than] 0.005; Sokal and Rohlf (1981)]. Thus, a population asymmetry parameter (PAP, Soule and Baker 1968) can be calculated. Because FA values are already size transformed, the leaf-trait FA values for each population were simply averaged to obtain PAP values (Table 1). Unlike Soule and Baker's (1968) method of summing the rank scores of the FA values, this average reflects the magnitude of the asymmetry. PAP is higher for population SS than SO, but similar between NS and NO.
TABLE 2. Multivariate analysis of variance (MANOVA) test of
differences between selfing and outcrossing populations in
fluctuating asymmetry (FA).

                            Trace       F       PR [greater than]

Southern populations
Within-leaf traits
Population                   0.56      4.09           0.023
Node                         1.83      3.37           0.0003
Between-leaf traits(*)
Population                   0.58      4.48           0.017
Node                         0.60      1.49           0.207
Northern populations
Within-leaf traits
Population                   0.19      0.597          0.673
Node                         0.10      0.288          0.880
Between-leaf traits(*)
Population                   0.09      0.25           0.901
Node                         0.74      7.24           0.005

* Between-leaf traits are those FA values calculated between
opposite leaves at the first three nodes of the plant.
TABLE 3. Total canonical structure coefficients for the fluctuating
asymmetry (FA) of each trait in each population. See Figure 1 for
explanation of the trait abbreviations.

              Total canonical                Total canonical
              structure                      structure
Trait         coefficient         Trait      coefficient

Southern populations

W1               0.336            SW1         0.078
V1               0.936            SV1         0.040
W2               0.088            SW2         0.023
V2               0.419            SV2         0.988

Northern populations

W1               0.564            SW1         0.782
V1               0.736            SV1         0.582
W2               0.526            SW2        -0.116
V2               0.245            SV2        -0.117


Sources of Developmental Stability

The three different measures of developmental stability used in this study (within-plant variance in leaf length, variance around a heteroblastic pattern, and FA) all showed a trend for the selfing, more homozygous populations to be less developmentally stable.

Using FA as an index of developmental stability, the southern selfing population (SS) was significantly more unstable than its neighboring outcrossing population (SO). These populations differ in outcrossing rate by a factor of 20, and in heterozygosity by a factor of two (Table 1; Holtsford and Ellstrand 1989). SS is completely inbred ([Mathematical Expression Omitted], Table 1; Holtsford and Ellstrand 1989). NS and NO did not differ significantly in FA but have only a threefold difference in outcrossing rate.

Fluctuating asymmetry differed significantly among nodes of the plant in both self-pollinating and outcrossing populations. Generally, nodes 7 and 15, in the middle portion of the plant, gave higher FA values than nodes l, 2, and 3. Other studies examining instability in upper, middle, and lower regions of the tobacco plant have found either that no differences in stability occur among regions (Sakai and Shimamoto 1965) or that the middle section is more stable (Paxman 1956). Transition regions between leaf or flower types, or from vegetative to reproductive nodes, are thought to be more variable (Williams 1965; Ellstrand et al. 1984). These regions may also be more developmentally unstable. Because [TABULAR DATA FOR TABLE 4 OMITTED] [TABULAR DATA FOR TABLE 5 OMITTED] different traits and different nodes gave different FA values in this study, we would recommend that several nodes always be used in plant FA studies to ensure detection of true levels of asymmetry.

Population level variance in leaf length was always greater in the selfing, more homozygous populations [ILLUSTRATION FOR FIGURE 2 OMITTED] and showed no relation to the allelic diversity of the populations ([Mathematical Expression Omitted] and PLP; Table 1). Patterns of population-level variance over the nodes of the plant changed from year to year in the same population, but in a very general way it can be said that the first and last nodes were the most variable. The nodes with highest FA (7 and 15) were not the nodes that exhibited the highest population-level variance in leaf length [ILLUSTRATION FOR FIGURE 2 OMITTED]. This discrepancy may reflect the fact that developmental instability is one of several sources of population level variance. Additionally, leaf-length stability is not well correlated with stability in other leaf traits. The FA values for different leaf traits were not significantly correlated. Independence of FAs for different traits within an organism is commonly found in animal studies (Soule and Baker 1968; Palmer and Strobeck 1986) and is an indication of the random nature of developmental instability. However, FA values for different traits are correlated at the population level in animals just as we found in this plant study (Soule and Baker 1968; Leafy et al. 1985; Palmer and Strobeck 1986). An FA study on tobacco found that instabilities were correlated within leaves and within flowers but not between leaves and flowers (Sakai and Shimamoto 1965).

Heslop-Harrison (1959) suggested that rate of development may influence developmental stability. A faster growth rate may result in more "developmental mistakes" and hence a decrease in developmental stability. Hill et al. (1992) found that plants from selfing populations of Arenaria uniflora grew faster than outcrossing plants and also showed a twofold increase in the infiorescence plastochron. In Arenaria, the selfing populations also displayed the most within-plant morphological variability (Hill unpubl. data). In our study, leaves on plants from the more homozygous, selfing populations grew at a slightly faster rate than leaves on outcrossing plants, but those leaves were produced at similar intervals (plastochrons) in both populations.

Measurement error in this study was between 12% and 20% of average FA, even though it was only 1-3% of average trait size. Many studies of developmental stability do not report measurement error (Palmer and Strobeck 1986). Clarke et al. (1992) report that measurement error was 7% of average FA values for Apis wing traits. One plant study reports consistency measures of up to 0.53 (Moller and Eriksson 1994) for petal measurements. Palmer (1994) discusses the impact of measurement error on FA and the need for its accurate estimation.

The Genetic Basis of Developmental Instability

Several factors are thought to decrease developmental stability: severe environmental stress (Bagchi and Iyama 1983; Parsons 1990, 1992; Graham et al. 1993), inbreeding in normally outcrossed organisms (Mitton and Grant 1984; Palmer and Strobeck 1986), unusually wide hybridizations (Palmer and Strobeck 1986; Ross and Robertson 1990), and strong [TABULAR DATA FOR TABLE 6 OMITTED] directional selection (Thoday 1955, 1958; Dun and Fraser 1959; Leamy and Atchley 1985). Likewise, if relaxed selection allows unfit or inbred organisms to remain in the population it could decrease average developmental stability. The highly variable phenotypes of many mutants are also expressions of developmental instability (Schmalhausen 1949: Dun and Fraser 1959; Waddington 1960; Maynard Smith et al. 1985; Crone and Lord 1993).

Two theories of the genetic basis of developmental stability explain these perceived patterns of instability (Clarke 1993). (1) Heterozygosity per se may increase developmental stability by increasing the physiological range over which the organism's enzymes are active or by increasing biochemical efficiency in some other manner (overdominance) (Robertson and Reeve 1952; Lerner 1954; Soule 1979). (2) Alternatively, according to the genic-balance theory, superior stability is due to complex epistatic interactions in coadapted gene complexes that have evolved along with the organism (Dobzhansky 1950, 1970; Mather 1953, 1973; Thoday 1955). Decreased stability would accompany inbreeding and outbreeding depression under this theory (Thoday 1958; Clarke et al. 1986). If developmental instability is a manifestation of inbreeding depression, then the arguments on the genetic basis of inbreeding depression, for example, enhanced expression of deleterious alleles in homozygotes or overdominante of heterozygotic loci in heterozygotes (Lynch 1991), might also explain the frequent association of developmental instability with lower levels of heterozygosity.

No simple relationship between heterozygosity level and FA was found in this study. Significant differences in FA were found between the southern populations that differed in heterozygosity by a factor of two, whereas the northern populations that have a 10-fold difference in heterozygosity are not significantly different in FA. That the southern selfing population (SS) is completely inbred ([Mathematical Expression Omitted], Table 1) and is significantly more unstable than any of the other populations leaves open the possibility that attaining a threshold level of homozygosity may cause the decrease in developmental stability (i.e., there is a dosage effect of the number of heterozygous loci; Waddington 1952, 1957; Thoday 1955). The greater stability of the closely related northern populations compared with the southern populations, also suggests that the northern populations share some genes in common that contribute to their stability.

Developmental Stability and Evolution

The evolution of selfing populations from outcrossing progenitors is an event that could be preceded or accompanied by decreased developmental stability. Maynard Smith et al. (1985) have hypothesized that, if there is selection for canalization, recently evolved phenotypes will display more variation than long-established phenotypes. Clarke and McKenzie (1987) have found empirical support for this in the evolution of pesticide resistance. Levin (1970a) discussed how a breakdown in buffering mechanisms in peripherally isolated populations might expose more variation to the action of natural selection, some of which might be advantageous to survival in the new peripheral environment and contribute to evolution in those populations. Selfing is the derived condition in Clarkia; and the selfing populations are more marginal (Vasek 1964). The two northern populations used in this study are genetically very similar and so may be a recently diverged pair (Futuyma 1986). Yet, these populations do not differ significantly in FA; there is even a slight trend for NS to be more stable than NO (Table 4). Increased FA may not necessarily accompany evolutionary divergence in Clarkia. Of course, the actual time since divergence is unknown and if, as Maynard Smith et al. (1985) have speculated, stability increases over time as populations became adapted to new environments, any instability that might have been involved in their divergence may have been selected away by now.

Other Stability Measures

This study has emphasized within-plant variation in leaf morphology. Other measures including clonal variability (Seburn et al. 1990; Barrett and Harder 1992), comparisons of well-characterized isogenic lines (Bagchi and Iyama 1983), and examination of other kinds of traits have the potential to indicate developmental stability. Physiological traits including anthocyanin content (Seyffert 1983) and variation in growth rates have also been used. Both positive and negative associations between variation in growth rates and levels of heterozygosity are known (Knowles and Mitton 1980; Knowles and Grant 1981; Ledig et al. 1983), but these studies have not factored out responses to widely varying environments at different locations as contributing to the observed variation in growth rates (except Strauss 1987). Lewontin (1956) and Allard and Bradshaw (1964) point out that for one trait to remain stable in a changing environment, other developmental processes must be labile. For stability to be maintained in morphological characters probably requires flexibility in physiological traits, like growth rates.

Because environmental stress also increases FA (Parsons 1990, 1992), growing the populations used in this study under a range of common environmental conditions might provide different results. We observed that patterns of population-level variance changed from year to year; thus, an environmental effect is expected. However, in both years the more homozygous, self-pollinating populations were the most variable for this population-level variance. Environment might affect only the magnitude of observed instability and not the population rankings in developmental stability.


We thank N. Ellstrand for suggesting the use of Clarkia tembloriensis for this project and T. Holtsford for providing the initial seed. We are grateful to N. Ellstrand, D. Reznick, D. Elam, and K. Eckard for their helpful comments on earlier versions of the manuscript. We also thank C. Adams, B. Beaver, R. Podolsky, D. Reznick, R. Shaw, and especially J. Semikoula for statistical and/or SAS advice.


Allard, R. W., and A.D. Bradshaw. 1964. Implications of genotype-environmental interaction in applied plant breeding. Crop Science 4:503-508.

Bagchi, S., and S. Iyama. 1983. Radiation induced developmental instability in Arabidopsis thaliana. Theoretical and Applied Genetics 65:85-92.

Bagchi, S. K., V. P. Sharma, and P. K. Gupta. 1989. Developmental instability in leaves of Tectona grandis. Silvae Gcnetica 38:1-6.

Barrett, S.C. H., and L. D. Harder. 1992. Floral variation in Eichhornia paniculata (Spreng.) Solms (Pontederiaceae). II. Effects of development and environment on the formation of selling flowers. Journal of Evolutionary Biology 5:83-107.

Chakraborty, R., and N. Ryman. 1983. Relationship of mean and variance of genotypic values with heterozygosity per individual in a natural population. Genetics 103:149-152.

Clarke, G. M. 1993. The genetic basis of stability. I. Relationships between stability, heterozygosity, and genomic coadaption. Genetica 89:15-23.

Clarke, G. M., and J. A. McKenzie. 1987. Developmental stability of insecticide resistant phenotypes in blowfly: a result of canalizing natural selection. Nature 325:345-346.

Clarke, G. M., G. W. Brand, and M. J. Whitten. 1986. Fluctuating asymmetry: A technique for measuring developmental stress caused by inbreeding. Australian Journal of Biological Science 39:145-153.

Clarke, G. M., B. P. Oldroyd, and P. Hunt. 1992. The genetic basis of developmental stability in Apis mellifera: Heterozygosity versus genic balance. Evolution 46:753-762.

Conover, W. J. 1980. Practical non-parametric statistics, 2d ed. Wiley, New York.

Crone, W., and E. M. Lord. 1993. Flower development in the organ number mutant clavata1-1 of Arabidopsis thaliana. American Journal of Botany 80:1419-1425.

Dobzhansky, T. 1950. Genetics of natural populations. XIX. Origin of heterosis through natural selection in populations of Drosophila pseudoobscura. Genetics 35:288-302.

-----. 1970. Genetics of the evolutionary process. Columbia University Press, New York.

Dobzhansky, T., and B. Wallace. 1953. The genetics of homeostasis in Drosophila. Proceedings of the National Academy of Sciences, USA 39:162-171.

Dun, R. B., and A. S. Fraser. 1959. Selection for an invariant character, vibrissa number in the house mouse. Australian Journal of Biological Science 12:506-523.

Ellstrand, N. C. 1983. Floral formula inconstancy within and among plants and populations of Ipomopsis aggregata (Polemoniaceae). Botanical Gazette 144:119-123.

Ellstrand, N. C., and R. J. Mitchell. 1988. Spatial and temporal patterns of floral inconstancy in plants and populations of Ipomopsis aggregata (Polemoniaceae). Botanical Gazette 149:209-212.

Ellstrand, N. C., E. M. Lord, and K. J. Eckard. 1984. The inflorescence as a metapopulation of flowers: Position-dependent differences in function and form in the cleistogamous species Collomia grandiflora Dougl. ex Lindl. (Polemoniaceae). Botanical Gazette 145:329-333.

Erickson, R. O., and F. J. Michelini. 1957. The plastochron index. American Journal of Botany 44:297-305.

Freeman, D.C., J. H. Graham, and J. M. Emlen. 1993. Developmental stability in plants: Symmetries, stress, and epigenesis. Genetica 89:97-102.

Futuyma, D. J. 1986. Evolutionary biology, 2d ed. Sinaur, Sunderland, MA.

Graham, J. H., D.C. Freeman, and J. M. Emlen. 1993. Developmental stability: A sensitive indicator of populations under stress. Pp. 136-158 in W. G. Landis, J. S. Hughes, and M. A. Lewis, eds. Environmental toxicology and risk assessment. American Society for Testing and Materials, Philadelphia, PA.

Heslop-Harrison, J. 1959. Variability and environment. Evolution 13:145-147.

Hill, J. P., E. M. Lord, and R. G. Shaw. 1992. Morphological and growth rate differences among outcrossing and self-pollinating races of Arenaria uniflora (Caryophyllaceae). Journal of Evolutionary Biology 5:559-573.

Holtsford, T.P., and N. C. Ellstrand. 1989. Variation in outcrossing rate and population genetic structure of Clarkia tembloriensis. Theoretical and Applied Genetics 78:480-488.

-----. 1992. Genetic and environmental variation in floral traits affecting outcrossing rate in Clarkia tembloriensis. Evolution 46: 216-255.

Huether, C. A., Jr. 1968. Exposure of natural genetic variability underlying the pentamerous corolla constancy in Linanthus androsaceus ssp. androsaceus. Genetics 60:123-146.

-----. 1969. Constancy of the pentamerous corolla phenotype in natural populations of Linanthus. Evolution 23:572-588.

Jinks, J. L., and K. Mather. 1955. Stability in the development of heterozygotes and homozygotes. Proceedings of the Royal Society of London B 143:561-578.

Johannsen, W. 1907. Does hybridization increase fluctuating variability? Pp. 98-113 in W. Wilks, ed. Royal Horticultural Society Report of the 3rd International Conference on Genetics (1906). Spottiswoode, London.

Knowles, P, and M. C. Grant. 1981. Genetic patterns associated with growth variability in Ponderosa pine. American Journal of Botany 68:942-946.

Knowles, P., and J. B. Mitton. 1980. Genetic heterozygosity and radial growth variability in Pinus contorta. Silvae Genetica 29: 3-4.

Leamy, L., and W. Atchley. 1985. Directional selection and developmental stability: Evidence from fluctuating asymmetry of morphometric characters in rats. Growth 49:8-18.

Leary, R. F., F. W. Allendorf, and K. L. Knudsen. 1985. Inheritance of meristic variation and the evolution of developmental stability in rainbow trout. Evolution 39:308-314.

Ledig, F. T., R. P. Guries, and B. A. Bonefeld. 1983. The relation of growth to heterozygosity in pitch pine. Evolution 37:1227-1238.

Lerner, I. M. 1954. Genetic homeostasis. Wiley, New York.

Levin, D. A. 1970a. Developmental stability and evolution in peripheral isolates. American Naturalist 104:343-353.

-----. 1970b. Developmental instability in species and hybrids of Liatrus. Evolution 24:613-624.

Lewontin, R. C. 1956. Studies on homeostasis and heterozygosity I. General consideration. Abdominal bristle number in second chromosome homozygotes of Drosophila melanogaster. American Naturalist 110:237-255.

Lynch, M. 1991. The genetic interpretation of inbreeding depression and outbreeding depression. Evolution 45:622-629.

Mather, K. 1953. Genetical control of stability in development. Heredity 7:297-336.

-----. 1973. Polygenic inheritance and natural selection. Biological Reviews 18:32-64.

Maynard Smith, J., and K. C. Sondhi. 1960. The genetics of pattern. Genetics 45:1039-1050.

Maynard Smith, J., R. Burian, S. Kaufmann, P. Alberch, J. Campbell, B. Goodwin, R. Lande, D. Raup, and L. Wolpert. 1985. Developmental constraints and evolution. Quarterly Review of Biology 60:265-287.

Mitton, J. B., and M. C. Grant. 1984. Associations among protein heterozygosity, growth rate, and developmental homeostasis. Annual Review of Ecology and Systematics 15:479-499.

Moller, A. P. 1992. Female swallow preference for symmetrical male sexual ornaments. Nature 357:238-240.

Moller, A. P., and M. Eriksson. 1994. Patterns of fluctuating asymmetry in flowers: Implications for sexual selection in plants. Journal of Evolutionary Biology 7:97-113.

Palmer, A. R. 1994. Fluctuating asymmetry analysis: A primer. Pp. 335-364 in T. A. Markow, ed. Developmental instability: Its origins and evolutionary implications. Kluwer, Dordrecht, The Netherlands.

Palmer, A. R. and C. Strobeck. 1986. Fluctuating asymmetry: Measurement, analysis, patterns. Annual Review of Ecology and Systematics 17:391-421.

-----. 1992. Fluctuating asymmetry as a measure of developmental stability: Implications of non-normal distributions and power of statistical tests. Acta Zoologia Fennica 191:57-72.

Parsons, P. A. 1990. Fluctuating asymmetry: An epigenetic measure of stress. Biological Reviews 65:131-145.

-----. 1992. Fluctuating asymmetry: A biological monitor of environmental and genomic stress. Heredity 68:361-364.

-----. 1993. Developmental variability and the limits of adaption: Interactions with stress. Genetica 89:245-253.

Patterson, B. D., and J. L. Patton. 1990. Fluctuating asymmetry and allozymic heterozygosity among natural populations of pocket gophers (Thomornys bottae). Biological Journal of the Linnean Society 40:21-36.

Paxman, G. J. 1956. Differentiation and stability in the development of Nicotiana rustica. Annals of Botany 20:331-347.

Robertson, F. W., and E. C. R. Reeve. 1952. Heterozygosity, environmental variability and heterosis. Nature 170:286.

Ross, K. G., and J. L. Robertson. 1990. Developmental stability, heterozygosity, and fitness in two introduced fire ants (Solenopsis invicta and S. richteri) and their hybrid. Heredity 64:93-103.

Rowe, P. R., and R. H. Andrew. 1964. Phenotypic stability for a systematic series of corn genotypes. Crop Science 4:563-567.

Roy, S. K. 1958. The regulation of petal number. Current Science 27:134-135.

Sakai, K., and Y. Shimamoto. 1965. Developmental instability in leaves and flowers of Nicotiana tabacum. Genetics 51:801-813.

SAS. 1985. SAS user's guide: Statistics. 5.0 ed. SAS Institute, Cary, NC.

Scheiner, S. M., R. L. Caplan, and R. F. Lyman. 1991. The genetics of phenotypic plasticity. III. Genetic correlations and fluctuating asymmetries. Journal of Evolutionary Biology 4:51-63.

Schmalhausen, I. I. 1949. Factors of evolution. Blakiston, Philadelphia, P.A.

Seburn, C. N. L., T. A. Dickinson, and S. C. H. Barrett. 1990. Floral variation in Eichhornia paniculata (Spreng.) Solms (Pontederiaceae): I. Instability of stamen position in genotypes from northeast Brazil. Journal of Evolutionary Biology 3:103-123.

Seyffert, W. 1983. Homeostasis in defined genotypes of Matthiola incana. Theoretical and Applied Genetics 64:205-212.

Sokal, R. R., and F. J. Rohlf. 1981. Biometry, 2d ed. Freeman, San Francisco, CA.

Soule, M. E. 1979. Heterozygosity and developmental stability: Another look. Evolution 33:396-401.

-----. 1982. Allomeric variation. 1. The theory and some consequences. American Naturalist 120:751-764.

Soule, M. E., and B. Baker. 1968. Phenetics and natural populations IV. The population asymmetry parameter in the butterfly Coenonympha tullia. Heredity 23:611-614.

Soule, M. E., and J. Cuzin-Roudy. 1982. Allomeric variation. 2. Developmental instability of extreme phenotypes. American Naturalist 120:765-786.

Steel, R. G. D., and J.H. Torrie. 1980. Principles and procedures of statistics. McGraw, New York.

Strauss, S. H. 1987. Heterozygosity and developmental stability under inbreeding and crossbreeding in Pinus attenuata. Evolution 41:331-339.

Thoday, J. M. 1952. Components of fitness. Symposia of the Society for the Study of Experimental Biology 7:96-113.

-----. 1955. Balance, heterozygosity and developmental stability. Cold Spring Harbor Symposia in Quantitative Biology 20:318-326.

-----. 1958. Homeostasis in a selection experiment. Heredity 12: 401-415.

Thornhill, R. 1992. Fluctuating asymmetry and the mating system of the Japanese scorpionfly, Panorpa japonica. Animal Behavior 44:867-879.

Van Valen, L. 1962. A study of fluctuating asymmetry. Evolution 16:125-142.

Vasek, F. C. 1964. The evolution of Clarkia unguiculata derivatives adapted to relatively xeric environments. Evolution 18:26-42.

Waddington, C. H. 1952. Canalization of the development of quantitative characters. Pp. 43-47 in E. C. R. Reeve and C. H. Waddington, eds. Quantitative inheritance. Stationary Office, London.

-----. 1957. The strategy of the genes. George Allen and Unwin, London.

-----. 1960. Experiments on canalizing selection. Genetic Research 1:140-150.

Williams, R. F. 1965. The shoot apex and leaf growth. Cambridge University Press, Cambridge.

Williams, W. 1960. Relative variability of inbred lines and hybrids in Lycopersicum esculentum. Genetics 45:1457-1465.

Zakharov, V. M. 1993. Appearance, fixation and stabilisation of environmentally induced phenotypic changes as a microevolutionary event. Genetica 89:245-253.
COPYRIGHT 1996 Society for the Study of Evolution
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 1996 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Sherry, Rebecca A.; Lord, Elizabeth M.
Date:Feb 1, 1996
Previous Article:Fertility selection on a discrete floral polymorphism in Clarkia (Onagraceae).
Next Article:Differing selection on plant physiological traits in response to environmental water availability: a test of adaptive hypotheses.

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters