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Keywords:

  • facultative adjustment;
  • lizard;
  • operational sex ratio;
  • sex allocation

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Bibliography

Mathematical models suggest that reproducing females may benefit by facultatively adjusting their relative investment into sons vs. daughters, in response to population-wide shifts in operational sex ratio (OSR). Our field studies on viviparous alpine skinks (Niveoscincus microlepidotus) document such a case, whereby among- and within-year shifts in OSR were followed by shifts in sex allocation. When adult males were relatively scarce, females produced male-biased litters and larger sons than daughters. The reverse was true when adult males were relatively more common. That is, females that were courted and mated by few males produced mainly sons (and these were larger than daughters), whereas females that were courted and mated by many males produced mainly daughters (and these were larger than sons). Maternal body size and condition also covaried with sex allocation, and the shifting pattern of sexual size dimorphism at birth may reflect these correlated effects rather than a discrete component of an evolved sex-allocation strategy.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Bibliography

Reproducing females of most animal species allocate approximately equal investment into the production of sons vs. daughters. However, the extensive theoretical literature on sex allocation identifies a number of situations in which parents can enhance their fitness by investing differentially in offspring of each sex. When fitness returns differ on parental investment into sons vs. daughters, these models predict that parents should adjust sex allocation accordingly (Fisher, 1930; Hamilton, 1967; Trivers & Willard, 1973; Charnov, 1982; Frank, 1990). Such skewed investment patterns are expected in several situations, most notably when sex allocation at the population level deviates from parity (causing frequency-dependent selection), when mating is nonrandom with respect to relatedness (e.g. inbreeding) and when there is significant asymmetry in relatedness with the offspring (e.g. via cytoplasmic inheritance or sex-linked genes).

Thus, when the fitness return on maternal investment is set by functions that differ in shape between sons and daughters, the null hypothesis is a deviation from Fisherian (equal) sex allocation (Charnov, 1982; Frank, 1987, 1990). Adjustment of sex allocation can involve shifts in the numbers of sons vs. daughters or in differential allocation of resources (e.g. energy and nutrients) per offspring. In either case, selection judges the success of a female’s allocation decision on the accumulated life-time reproductive success of her offspring. The mechanisms by which sex ratios could be skewed remain controversial, but might involve environmental sex determination (Bull, 1980), an obligate (50 : 50) primary sex ratio that is later modified by selective abortion or resorption (e.g. Trivers & Willard, 1973) or direct genetically determined shifts to the sex ratio at conception (Myers, 1978).

Most models within this field deal with sex-allocation shifts in response to variation in spatial or parental resources (Trivers & Willard, 1973; Clutton-Brock & Iason, 1986; Clutton-Brock, 1986). However, sex-specific fitness functions may also vary in time within a single population, raising the possibility that females evolve the ability to facultatively track such changes and adjust their sex-allocation strategies accordingly. This possibility is explored in Werren & Charnov’s Perturbation Model (1978), which suggests that a period of male rarity may induce a (facultatively adjusted) male-biased sex ratio in the following generation. The model rests on the assumption that the adult sex ratio at conception is correlated with the offspring’s future reproductive success and is applicable in situations of overlapping generations, when parents are genetically able to adjust the sex ratio of clutches and when differential temporal patterns in life history expectations exist for the offspring of the two sexes. Many animal and plant species meet these assumptions and stable age distributions and tertiary sex ratios (i.e. the sex ratio at the population level) are probably rare in the wild. Thus, the perturbation model was an important advancement because it put facultative sex ratio adjustment into a formalized framework for a wide range of taxa under realistic conditions.

Since 1978, several examples have accumulated that support some of the predictions generated by Werren & Charnov. For example, female Seychelle warblers produce sex ratios that covary with the availability of territories and, hence, breeding opportunity of sons (Komdeur et al., 1997). Similar adjustments in the numbers and/or relative sizes of sons and daughters have been empirically confirmed in response to (i) population-shifts in sex ratio in humans (Lummaa et al., 1998), (ii) mate quality in birds (Burley, 1986; Ellegren et al., 1996; Svensson & Nilsson, 1996) and (iii) sex-specific fitness effects of body size in mammals (Clutton-Brock et al., 1982; Molumby, 1996; for recent reviews see Ellegren & Sheldon, 1997; Oddie, 1998; Sheldon, 1998).

The scarcity of examples may reflect logistical problems rather than a genuine lack of generality of this phenomenon. To test aspects of sex allocation theory, we need information on variation in demography and sex ratios of the adult population and to be able to determine the sex of offspring very early in their development – and this poses a substantial difficulty in many kinds of organisms. For example, sexing hatchling birds was difficult until the recent development of molecular markers (Ellegren, 1996). In contrast, neonatal males of many squamate reptile species have eversible hemipenes and thus are easily sexed at parturition (Harlow, 1996). Despite this advantage, reptiles with genetic sex determination have rarely been exploited as models for the study of sex allocation. Nonetheless, there are indications that sex ratios at hatching or parturition can sometimes deviate from parity in such species, either in the overall population (Shine & Bull, 1977), or as a function of maternal body size (Dunlap & Lang, 1990) or age (Madsen & Shine, 1992).

In the present study, we take advantage of the ease of sexing lizard offspring at parturition to test Werren & Charnov’s (1978) hypothesis that mothers may facultatively shift their sex-allocation patterns in response to temporal variation in populational sex ratios.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Bibliography

Field and laboratory techniques

The model organism

Snow skinks (Niveoscincus macrolepidotus) are small (to 5 g) ground-dwelling lizards that mature at the age of ca. 3 years and live to a maximum age of ca. 10 years (Olsson & Shine, 1999a, b). They belong to a matrotrophic lineage (Stewart & Thompson, 1994) and although the yolk present in the egg cell at ovulation supports most of embryonic development, females of these species provide additional (placental) nutrients through the prolonged (>12-month) gestation period (Olsson & Shine, 1999a). Female snow skinks maintain fully developed young in the uterus through hibernation and hence can time parturition to coincide with favourable spring conditions that enhance offspring survival (Olsson & Shine, 1999b). This maternal ability to retain full-term young may enable females to fine-tune resource allocation to their offspring.

We studied sex allocation in a natural population of snow skinks at the summit of Mt Wellington, Tasmania from 1994–1995 until 1996–1997 (heretoforth referred to as seasons 1 to 3). In early spring, females occur in two reproductive stages. Either they are close to ovulation or close to parturition. This is the result of their prolonged gestation period and biennial to triennial reproduction (Olsson & Shine, 1999a). Females early in their reproductive period (i.e. close to ovulation) display characteristic abdominal scars that result from the male holding her in his jaws during copulation. By counting these scars, we can estimate the number of copulations per female. At the end of the gestation period, however, these copulatory marks have faded.

Werren & Charnov’s (1978) hypothesis predicts adjustment of sex allocation in response to temporal variation in operational sex ratio (OSR), defined as ‘the number of sexually active males in relation to the number of receptive females at any given time’ (Emlen & Oring, 1977). To make a direct comparison possible between OSR and offspring sex ratios expressed in percentage sons of a clutch, we also calculated OSR in percentage males of the study population (i.e. no. males/(no. males + no. females) × (100). We quantified OSR and offspring sex ratios at two temporal scales: (i) among seasons and (ii) within seasons, as changes in offspring sex ratios in 10-percentiles of the time period (days) over which females gave birth and the corresponding OSRs in the previous year (gestation is ca. 13 months). The 10% limit was arbitrarily chosen and represents approximately 1 week and in the second interval of the second season no births were recorded (i.e. n=29 for the pooled three seasons). Both these scales of comparison are of interest, because OSR can change markedly within as well as among seasons (Madsen & Shine, 1992). For the calculation of both estimates of OSR, we exploited the fact that males produce spermatozoa throughout the mating season (Olsson et al., 1999) and, hence, OSR is set by the number of females that are sexually receptive (engage in matings) in relation to an approximately constant number of males (i.e. the number of sexually mature males in the population). In the third season, our sample sizes of both males and females were substantially lower than in the first 2 years. This is partly explained by more frequent rains than in the previous 2 years, which is likely to have both increased lizard mortality and reduced the opportunity for us to sample the populations. However, there is no reason to believe that the probability of sighting males relative to females would be any different in that year than in other years, hence, OSR should be estimated with the same accuracy in all 3 years. To look for among-year shifts in OSR, we used χ2 tests on number of males vs. number of females. To confirm that indeed shifts in OSR results in different numbers of copulations per female, we tested for differences in mating scars per female in the different years.

Females were caught by hand or by noose and brought back to the laboratory to await parturition. Female snout-vent length (SVL) and total length were measured to the nearest millimetre whereafter the female was weighed to the nearest 0.1 g and residuals from mass – SVL regressions were used as seasonal condition indices. Each female was assigned to an individual cage (5 cm × 15 cm × 25 cm) in a rack with a heating element running along the back of the cage. The females’ cages were checked for newborns at least twice daily. Neonates were measured and weighed as described for females and sexed by gently sliding a V-shaped prong along the tail base towards the cloaca. This procedure reliably everts the two hemipenes in males (Olsson & Shine, 1999b). The young were separated from the female (there is no parental care in this species) were then kept in 120 mm × 100 mm × 35 mm cages until release at the study site within 1 week of parturition (awaiting the first day with suitable weather).

Statistical analyses

When females produced more than one offspring of each sex, we calculated mean values per offspring sex of trait values before submitting them to statistical analysis. In no year was there a significant correlation between litter size and offspring size (litter size ranges, 1–5 in season 1, 1–4 in season 2 and 3; Table 1). Because we did not originally envisage an overall analysis of sex allocation, data on some of the traits in this study (e.g. copulation scars) are missing from some sampling periods. Therefore, sample sizes vary to some degree among analyses.

Table 1.  Number of sons and daughters produced in clutches of different sizes in the different years. The first number given in each category represents the number of sons in a given category, the second number represents the number of daughters and the number immediately to its right the number of females producing this clutch size. Thumbnail image of

Because adaptive sex allocation may depend on litter size (Frank, 1990), we examined the degree to which clutches of different sizes contributed to among-year shifts in sex ratio. To do this, we tested the observed sex ratio against theoretical predictions from a (binomial) null hypothesis of equal probability (P=0.5) that an ovulation will result in a son (S) or a daughter (D). Mothers producing three young, for example, will then fall into four categories: those producing all sons, all daughters and those with two offspring of one sex and one of the other. The frequencies of mothers in each of these categories can be calculated from (S + D)3 (i.e. S3 + 3S2D + 3SD2 + D3=1, i.e. 0.125 + 0.375 + 0.375 + 0.125 (disregarding birth order)). For example, with equal probability of either sex (S=D=0.5), 12.5% of mothers are expected to produce only sons.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Bibliography

Among-year shifts in sex allocation

Females could modify their sex-specific investment either (1) by changing the sex ratio of offspring in litters or (2) by changing the relative sizes of sons vs. daughters. Our snow skink population exhibited both of these shifts:

Sex ratio

The sex ratio at parturition in the population shifted by 15%, from a female bias (46% sons) in season 1 to a male bias (61% sons) in season 3 (χ2=8.08, d.f.=2, P=0.028, all three seasons included). When the proportion of litters with a female vs. male bias in sex ratio was considered, the shift in sex ratios between seasons was even more pronounced (Fig. 1). Females producing a litter size of one (n=40), four (n=11) and five young (only one female), respectively, contributed only marginally to shifts in the average sex ratio at parturition (Table 1). These females produced a small proportion of the annual cohort (ca. 15–18% year−1) and their litters exhibited relatively even sex ratios (1 : 1 in three cases out of seven; Table 1). Thus, the among-year shift in the secondary sex ratio at the population level was caused by a biased production of sons vs. daughters by mothers with litter sizes of two to three young ones. Their neonates comprised ca. 85% of all offspring (Table 1; 46–64% sons year−1).

image

Figure . 1. Annual variation in the proportion of female snow skinks giving birth to litters with a secondary sex ratio biased towards daughters vs. sons, across the three seasons (years) of our study.

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χ2 Tests identified four deviations of observed sex ratios from 50 : 50 (Figs 2, 3): (i) Females with a litter size of three over-produced daughters (two daughters, one son) in the first season (ii) more females with a clutch size of both two and three young produced more ‘all son’ litters in the last season and (iii) in the second season, more two-offspring litters contained one offspring of either sex than expected by chance.

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Figure . 2. Females with a litter size of two young that produced biased sex ratios, expressed as deviations from the number of females in the population predicted to do so from binomial, random expectations. Each season (1–3 on the x axis), is represented by a cluster of five columns. The left three represent litters with all son vs. all daughter litters; the outer ones depicting the empirically found number of females, contrasted against the theoretically predicted number of females in the centre column. The remaining two right columns in each five-column per season cluster represent the theoretically predicted number of females producing an even sex ratio (left column) contrasted against the empirically found (right column). In the second season, more females than expected by chance produced an even sex ratio (χ2=4.0, P=0.046, d.f.=1). In the third season, more females than expected by chance produced all-son clutches (χ2=6.6, P=0.01, d.f.=1).

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image

Figure . 3. Females with a litter size of three young that produced biased sex ratios, expressed as deviations from the number of females in the population predicted to do so from binomial, random expectations. Each season (1–3 on the x axis) is represented by a cluster of six columns. The left three represent litters with all son vs. all daughter litters; the outer ones depicting the empirically found number of females, contrasted against the theoretically predicted number of females in the centre column. The remaining three right columns in each six-column per season cluster represent the theoretically predicted number of females producing a female-biased [2(D):1(S); left column] vs. a male-biased [2(S):1(D); right column] litter, contrasted against the theoretically predicted number (centre column). In the first season, more females than expected produced a daughter-biased sex ratio (two daughters and one son; χ2=4.3, P=0.038, d.f.=1). In the third season, more females than expected by chance produced all-son clutches (χ2=17.3, P < 0.001, d.f.=1).

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Offspring mass

Two-factor ANOVAs with season and litter size as factors and offspring mass as dependent variable revealed a highly significant effect of year for both sons and daughters (Type III F[2,158]=33.1, P=0.0001 and F[2,135]=43.8, P=0.0001, sons and daughters, respectively), but with a nonsignificant effect of litter size (F[2,158]=0.93, P= 0.337 and F[2,135]=0.86, P=0.354, sons and daughters, respectively).

We then compared mass at birth between all-son vs. all-daughter litters (Fig. 4). We first looked for a significant interaction term between sex ratio category and season, which proved highly significant (F[5,119]=18.1, P=0.0001). Thus, offspring mass was linked to the sex ratio of the litter but in different ways in different seasons. However, we were also interested in demonstrating the specific direction in which mass was skewed to sons vs. daughters depending on the season. We therefore also performed specific tests with the data set for each season. In the first season, offspring from all-female clutches weighed an average of 0.41 g (±0.01 SE, n=19), whereas offspring from all-male clutches weighed an average of 0.38 g (±0.10 SE, n=17). This difference was statistically significant (Kruskal–Wallis test with χ2 approximation, χ[1]2=4.1, P=0.042). In the third season, the reversed result was observed. Males weighed an average of 0.32 g (±0.01 SE, n=36) and females 0.30 g (±0.01 SE, n=16), bordering on statistical significance (Kruskal–Wallis test with χ2 approximation, χ[1]2=3.70, d.f.=1, P=0.054). In the second season, the corresponding analysis was not statistically significant (Fig. 4; χ[1]2=1.38, P=0.24).

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Figure . 4. Differences in body mass of neonatal snow skinks between all-daughter vs. all-son clutches across the three seasons of our study.

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Effects of OSR on offspring sex ratio

Seasonal OSR varied significantly from 68% males [140(F) : 293(M)] in the first year, to 60% in the second year [185(F) : 272(M)] and 54% males [100(F) : 119(M)] in the third year (χ[2]2=12.47, P=0.002). Thus, the offspring sex ratio (above) varied with OSR as predicted by the Werren–Charnov hypothesis. The low sample size of seasons (n=3) precluded any statistical test of between-season shifts in offspring sex ratio vs. OSR. Our within-season (between 10 Percentiles) data, however, allowed such an analysis. OSR for the 10 percentiles of the receptivity seasons (standardized by season, because OSR differed between years) were significantly correlated with the corresponding mean secondary sex ratios (assigning 0 to daughters and 1 to sons). Females that had been courted and/or copulated by fewer males produced relatively more sons (Fig. 5; rs=0.43, P=0.019, n=29; there were no births in interval 2, season 2).

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Figure . 5. Correlation between estimates of OSR in 10-percentile segments of the mating season and the proportion of sons produced in this segment of the mating season in the following year (rs=0.43, P=0.019, n=29; in percentile 2, season 2 there were no parturitions).

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Through the receptivity period, there was a significant negative correlation between mean date of an interval and mean female condition (rs=−0.39, P=0.03, n=30). However, neither mean female condition nor mean date in interval was significantly correlated with mean secondary sex ratio (rs=0.02, P=0.93 and rs=0.30, P=0.12, respectively; n=30). Because both female condition and date within the mating season have been identified as strong determinants of offspring sex ratios in some other species (Frank, 1990), we also looked for effects of these traits when factoring out the effect of OSR in a partial correlation analysis. Neither mean date of the percentile nor mean female condition was significantly correlated with mean offspring sex ratio when the effect of OSR was statistically removed (rs=0.30, P=0.14 and rs=0.13, P=0.49, n=29). The corresponding correlation coefficient between operational sex ratio in the interval and mean offspring sex ratio, however, remained significant when mean date of season and mean female condition were held constant in a partial correlation analysis (rs=0.48, P=0.01, n=29).

Male attraction to females with large litters: a possible link between OSR, offspring sex ratio and relative size of sons and daughters

Because there was no difference in offspring size between litters of two vs. three offspring, we pooled these data and looked for differences in maternal traits depending on whether females produced a female-biased or male-biased clutch. A combined test demonstrated significant interactions between sex ratio category and season on female mass (F[5,120]=3.2, P=0.009) whereas the corresponding test with female condition as dependent variable fell short of statistical significance (F[5,120]=1.9, P=0.096). However, we were not only interested in demonstrating shifts in sex ratios between female traits and seasons, but also in looking for the direction of such shifts depending on which season we specifically analysed. In the first season, females that produced more daughters than sons were significantly heavier than females that produced more sons than daughters (mean female mass 3.94 ± 0.09 SE, n=25; 3.59 ± 0.14, n=14, respectively; t=2.2, P=0.036, d.f=37). In the first season, females producing more daughters tended to be in better condition than females producing more sons, but this result fell short of statistical significance (t=1.7, P=0.098, d.f.=37). In the third season (when more sons than daughters were produced overall), the reverse situation occurred. That is, females that produced more sons than daughters were in better condition than those that produced more daughters than sons (mean female condition 0.07 ± 0.06 SE, n=39; −0.24 ± 0.13, n=17, respectively; t=2.4, P=0.026, d.f.=54). In this third season, the difference in mass between females producing relatively more sons than daughters fell short of statistical significance (P=0.14).

A female’s postpartum mass was correlated with the mean mass of her offspring (r=0.24, P=0.0002, n=234, data standardized by season and then pooled). Furthermore, larger females produced larger litters (rs=0.57, P=0.0001, n=227) and females with larger litters had more mating scars (rs=0.21, P=0.0001, n=179, see further below). Because these large females attract more courtship and copulation, we might expect them to respond more strongly to shifts in OSR than do less fecund conspecifics. Furthermore, females copulated more often in the first than in the last season, based on mating scars (using one observation per female and season, averages of 1.4 ± 0.14, n=121 vs. 0.97 ± 0.18, n=67; F[2,186]=4.2, P= 0.043).

The higher mating frequency of larger females suggests a straightforward mechanism by which mean offspring mass might be tied to numerical sex allocation. If more fecund and thus more attractive females display a stronger facultative response to OSR, then we would expect that these animals would produce more highly skewed sex ratios. These females also tend to produce large offspring. Hence, we would see a pattern whereby, whichever sex of offspring was over-produced in a given year would also tend to be heavier at birth than the under-produced sex. We can test this prediction by classifying litters with respect to sex ratio (male, female and no bias) and examining whether mean offspring mass is affected not only by season, but also by an interaction between sex ratio category and season. Analysis supports this prediction, as the interaction season × sex ratio category was highly significant (F[8,236]=19.0, P=0.0001, r2=0.39).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Bibliography

Our analysis demonstrates a temporal (among-year) shift in sex allocation by female snow skinks. More daughters than sons were produced after mating seasons when adult males were common whereas more sons than daughters were born after mating seasons when adult males were rare. Additionally, within each season, the sex that was over-produced tended to be larger at birth on average, than the under-produced sex. Our data further suggest that the causal mechanism linking adult sex ratio (OSR) to maternal sex allocation may involve the female’s experiences during the mating season. If a female is courted and mated by several males, she may thereby tend to overproduce daughters in her next litter. Thus, female snow skinks show facultative sex allocation adjustment in accord with the general predictions of Werren & Charnov’s (1978) Peturbation model.

Because females lose their copulation scars during gestation, we cannot link the number of copulations by a female directly to the sex ratio of her offspring. Three observations, however, suggest that this sequence of events comprises a causal link to skewed offspring sex ratios: (i) the tertiary sex ratio and offspring sex ratio shifted in opposite directions over the three seasons of our study, (ii) females mated more often in a year when the OSR was more male-biased and (iii) most importantly, within seasons we detected a strong correlation between the OSR experienced by a female and the proportion of sons that she later produced. Further, our data suggest that maternal body size may play an important role in this chain of events. Because larger more fecund females attract higher levels of courtship and mating than do smaller females, the larger animals may be more sensitive to shifts in OSR. Shifts in OSR may be less easy to perceive for females in which males show less interest. In keeping with this hypothesis, the offspring from single-young litters displayed a 50 : 50 sex ratio in all 3 years (Table 1).

The mechanism by which female snow skinks modify their sex allocation remains unclear. The mode of sex determination in this species is not known, raising the possibility that females can somehow modify the primary sex ratio of their litter. In keeping with this suggestion, recent laboratory studies on a congeneric species have reported that maternal basking treatments can modify sex ratios at birth (E. Wapstra, unpublished). However, closely related species possess heteromorphic sex chromosomes and thus, genetic sex determination (GSD; Donellan, 1985). Even with GSD, a female might still be able to control primary sex ratio by selective use of sperm (Olsson & Madsen, 1998). The alternative mechanism of selective abortion seems less plausible in reptiles (Blackburn, 1998) and in support of this suggestion we have never seen any evidence of females giving birth to dead eggs or embryos.

Although our data conform to predictions from Werren and Charnov’s model, we do not have any direct measures of reproductive success accruing from the production of sons vs. daughters. Because neonatal snow skinks require about 3 years to mature (M. Olsson and R. Shine, unpublished), the OSR at the time of a lizard’s conception may offer only an approximate guide to the likely OSR that it will encounter as a breeding adult. Nevertheless, a female strategy that adjusts sex allocation relative to current OSR may be better than one that makes no such adjustment.

Our analyses suggest that reproducing female snow skinks may modify their allocation per offspring, as well as the overall sex ratio of their litter. The general pattern was that females invested more per son in the year when they overproduced sons and invested more per daughter in the year when they overproduced daughters. Because the Werren-Charnov model is framed in terms of overall allocation, this kind of correlation between sex ratio and relative offspring size is as predicted by their model. That is, shifts in sex allocation are manifested by concurrent shifts in the number and relative size of male vs. female offspring. Although this result thus accords with prediction, our data on other correlates of offspring size suggest that causal mechanisms may be complex. For example, if larger females tend to (i) produce larger offspring and (ii) are more attractive to males and thus perceive the local OSR as more highly male-biased, then an adaptive matching of litter sex ratio to OSR will also generate a correlation between litter sex ratio and mean offspring size. Hence, correlations between sex ratio and sex differences in offspring size may be generated by some third variable (such as maternal body size) rather than comprise independent components of some maternal sex allocation strategy.

In combination with previous work, our study suggests that squamate reptiles may prove to be useful ‘model organisms’ for studies on sex allocation. Previous work has shown that reproducing female reptiles can manipulate sex allocation in temperature-dependent sex determination species (Bull, 1980) and that maternal nest-site choice can differentially affect fitness-associated traits of sons vs. daughters (Burger & Zappalorti, 1988; Elphick & Shine, 1998). Given the diversity in sex-determining systems within squamates and the ease of sexing offspring at birth, these organisms may prove to be ideally suited for more detailed examination of the ways in which reproducing organisms allocate resources differentially among male and female offspring.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Bibliography

We thank the Australian Research Council and the Swedish Natural Science Research council for supporting this project financially, Lollo Ba’k-Olsson and Tobbe Helin provided excellent field assistance and the Wilkes families gave logistical support.

Bibliography

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Bibliography
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