Sperm competition effects on sperm production and expenditure in sailfin mollies, Poecilia latipinna

Behavioral Ecology doi:10.1093/beheco/arm044 Advance Access publication 12 June 2007 Sperm competition effects on sperm production and expenditure in...
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Behavioral Ecology doi:10.1093/beheco/arm044 Advance Access publication 12 June 2007

Sperm competition effects on sperm production and expenditure in sailfin mollies, Poecilia latipinna Andrea S. Aspbury Department of Biology, Texas State University-San Marcos, San Marcos, TX 78666, USA Sperm competition risk (SCR) models predict that if there is a low probability a male’s ejaculate will compete with another male, individuals should invest less sperm in a mating, whereas if the probability of competition is high, males should invest more sperm. Alternatively, models of sperm competition intensity (SCI) predict that increased intensity of sperm competition leads to maximal sperm investment when a male faces a single competitor. Few studies have examined predictions of these models for males of varying size, and none have examined effects of sperm competition on both sperm production and expenditure. To examine effects of sperm competition on these variables, male sailfin mollies (Poecilia latipinna) from 3 size classes were randomly assigned to one of 3 treatments that manipulated SCR and SCI: 1) no risk, low intensity; 2) risk present, medium intensity; and 3) risk present, high intensity. Male sailfin mollies produced more sperm in the high-intensity treatment than in the low-intensity treatment. Sailfin mollies in the risk present treatments expended more sperm than those males in the risk absent treatment. There was no significant difference in sperm expenditure between the medium intensity and the high-intensity treatment, indicating that maximal sperm investment does not occur when the number of competing males is one. Furthermore, small males expended more sperm than medium and large males. These results suggest that male sailfin mollies respond as predicted to SCR, but not to SCI. I suggest that male size effects and sperm production should be considered in theoretical treatments of optimal male sperm investment strategies. Key words: cryptic male choice, livebearing fish, operational sex ratio, strategic allocation. [Behav Ecol 18:776–780 (2007)]

perm competition occurs when the sperm from two or more males compete to fertilize the eggs of a female (Parker 1970). Interspecific comparisons have yielded generally consistent patterns concerning male reproductive anatomy, physiology, and behavior across diverse taxa in response to sperm competition (reviews: Smith 1984; Birkhead and Møller 1998; Simmons 2001; Wedell et al. 2002). For example, males in species with high sperm competition have larger testes and/or greater sperm numbers (mammals: Harcourt et al. 1995; fish: Stockley et al. 1997; insects: Sva¨rd and Wiklund 1989; Gage 1994), more motile sperm (birds: Birkhead et al. 1999), and shorter intervals between ejaculations (mammals: Stockley and Preston 2004) than those species with less sperm competition. When considering male reproductive physiology and behavior at the intraspecific level, 2 general models make different predictions. The sperm competition risk (SCR) models (Parker et al. 1997) (where risk is defined as the probability that the ejaculates of the 2 different males will compete for access to a female’s eggs) predict that if there is a low probability that the males’ ejaculates will compete, individual males should invest less in each mating, whereas if the probability of competition is high, males should invest more (increase ejaculate size) in each mating (Parker et al. 1997; Parker 1998). Under the sperm competition intensity (SCI) models, where intensity is defined as the number of males competing for the same clutch of eggs, males are predicted to have smaller ejaculate sizes as the number of competing males increases beyond one competitor (Parker et al. 1996; Parker 1998). Under SCI models, SCR must be high, given that the

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Address correspondence to A.S. Aspbury. E-mail: aspbury@txstate. edu. Received 15 December 2006; revised 20 March 2007; accepted 9 April 2007.  The Author 2007. Published by Oxford University Press on behalf of the International Society for Behavioral Ecology. All rights reserved. For permissions, please e-mail: [email protected]

probability of competing ejaculates will be certain (at intensity of one or greater) (delBarco-Trillo and Ferkin 2006). There have been numerous tests of the SCR and SCI models developed by Parker et al. (1996, 1997) (reviews: Birkhead and Møller 1998; Engqvist and Reinhold 2005). Recently, support for both the SCR and SCI models has been found by Pizzari et al. (2003), in which the authors examined sperm expenditure in male jungle fowl (Gallus gallus) of different social status. They demonstrated that dominant males increased sperm expenditure with increasing SCR and SCI from the lowest expenditure with no competing males, intermediate expenditure with one competing males, and highest expenditure with 3 competing males. However, subordinate males only increased sperm allocation between low and intermediate sperm competition and decreased investment at high levels of sperm competition, which supports the prediction of the Parker et al. (1996) SCI model (Pizzari et al. 2003). In other taxa, tests of models of sperm allocation under SCI provide conflicting results: In rainbow darter (Etheostoma caeruleum), males do not tailor their sperm allocation to increasing SCI (Fuller 1998), whereas a study of male bitterling (Rhodeus sericeus) (Candolin and Reynolds 2002) and a study of black gobies (Gobius niger) and grass gobies (Zosterisessor ophiocephalus) (Pilastro et al. 2002) do support the SCI model of Parker et al. (1996). The many studies of sperm competition in externally fertilizing fish species have generated debate concerning the predictions of the SCI models (review in Petersen and Warner 1998). Although the SCI model (Parker et al. 1996) was originally developed for externally fertilizing taxa, the predictions of the model should not differ for internally fertilizing taxa if multiple males mate with the same female in temporal proximity (Parker 1998). However, very few studies have examined sperm competition in fish species with internal fertilization. As shown in recent studies (e.g., Evans et al. 2003), it is

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Sperm competition in sailfin mollies

relatively easy to both manipulate and assess the level of sperm competition in internal fertilizers. For example, in the livebearing fish, Gambusia holbrooki, individual males invest more sperm under high risk than under low risk (Evans et al. 2003). In addition, Evans et al. (2003) report that the results of the study were not due to variable sperm production prior to mating, which is a variable that needs to be controlled for when analyzing sperm competition models (Engqvist and Reinhold 2005). Furthermore, although Evans et al. (2003) statistically controlled for variable male size (and hence sperm production abilities), they were unable to analyze the effects of variable male size on sperm expenditure. The results of Pizzari et al. (2003) suggest that the effects of sperm competition on sperm allocation should be analyzed for males of varying quality and/or size. In this study, I examined whether male size and SCR and SCI directly affect the priming response (physiological changes associated with sperm production when males are provided with stimuli from females [Olse´n and Liley 1993; Bozynski and Liley 2003]) and sperm expenditure during mating in the sailfin molly, Poecilia latipinna. Testing effects of SCR and SCI on sperm priming immediately preceding mating is important, as such short-term physiological responses may provide the reason why some tests of SCI do not meet the predictions of the SCI model of Parker et al. (1996). Sailfin mollies live in shoals comprising 10–20 individuals of both sexes. Therefore, in natural populations, males and females have the opportunity to observe other individuals during mating (Witte and Ryan 2002; Aspbury AS, personal observation). Male P. latipinna shows continuous variation in standard length (SL—tip of snout to caudal peduncle), and this size variation is associated with Y-chromosome–linked alleles (Travis 1994). Larger males exhibit higher rates of courtship displays to females, whereas smaller males attempt inseminations without courtship at a higher rate (Farr et al. 1986; Travis et al. 1990; Travis 1994; Travis and Woodward 1989). Male sperm production also varies with male size; Aspbury and Gabor (2004) showed that although larger males have higher sperm counts in the absence of female stimuli, small males show the greatest priming response compared with intermediate and large males. This result suggests that sperm production is costly and may be more costly for smaller males. Therefore, smaller males may show a stronger response than larger males in the face of SCR and SCI (e.g., a greater increase in sperm expenditure in the presence of high SCR and intermediate SCI). Here I tested the hypotheses that sperm priming and expenditure are influenced by both SCR and SCI, by manipulating the operational sex ratio (OSR), which has been shown to affect male investment in ejaculate size (Gage 1991; Gage and Baker 1991; delBarco-Trillo and Ferkin 2006).

METHODS Sailfin mollies used in the following experiment were collected during May 2004 and May–June 2005 from a population in the headwaters of the San Marcos River in Hays County, Texas. Females and males were housed separately in 38-l tanks for at least 30 days prior to the experiments to ensure that none of the females were gravid. The females were tested in the following experiment independent of their reproductive cycles, and no females were obviously gravid. Fish were fed O.S.I. Spirulina Flake mixed with O.S.I. Freshwater Flake food (Ocean Start International Marine Laboratory Inc., Hayward, CA) and supplemented with live brine shrimp and maintained on a 14:10 h light:dark cycle. On day zero of the experiment, I removed the focal males from their stock tank and measured male SL. I divided the

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focal males into 3 size class groups based on the overall SL distribution of this population such that N ¼ 15 for each size class (mean 6 standard error [SE] [mm]: small ¼ 25.80 6 0.34; intermediate ¼ 31.20 6 0.82; large ¼ 43.95 6 1.81). After I measured males, I stripped sperm following established protocols (Aspbury and Gabor 2004) and placed the individual focal males in separate 18-l tanks, each divided into 2 sections by a clear Plexiglas divider. The dividers were not sealed to the tank, allowing access to both visual and chemical cues. I then placed a female (mean 6 SE [mm]: SL ¼ 33.77 6 0.26) in each focal male tank on the opposite side of the divider. For each size class, I assigned 5 of the 15 males randomly to either one of 3 treatments that varied in the number of each sex of the stimulus fish: 1) low SCI and SCR absent treatment (N ¼ 4 females, N ¼ 0 males); 2) medium SCI treatment and SCR present (N ¼ 3 females, N ¼ 1 male); or 3) high SCI treatment and SCR present (N ¼ 1 female, N ¼ 3 males). I placed the stimulus fish in a smaller tank (5.27 l) that was placed adjacent to the focal fish tanks. The stimulus females were chosen such that the mean 6 SE (mm) of SL ¼ 31.2 6 2.0 and the mean 6 SE (mm) of SL of the stimulus males was 31.9 6 1.9. None of the stimulus fish were used more than once as stimulus fish, and none of the stimulus fish were used as focal males or females. On day 7 of the experiment, I stripped sperm from all males again. The priming response was defined as the difference in day 7 sperm counts to day 0 sperm counts (Aspbury and Gabor 2004). I placed the male back in his tank for 3 more days to allow the male to replenish sperm stores. During this 3 day replenishment period, an opaque divider was placed between the stimulus fish tanks and the focal fish tanks. On day 10 of the experiment, I removed the opaque divider between the 2 tanks, as well as the divider from the test tank and allowed the focal male and female to physically interact for a period of 10 min, during which I recorded the number of mating attempts (gonopodial thrusts) directed at the female. After this mating trial, I again stripped all the sperm remaining in the males. I counted all sperm cell samples 5 times on an improved Neubauer chamber hemocytometer (Reichert, Buffalo, NY) under 4003 magnification. The total number of sperm cells was determined by multiplying the mean cell count by the sample’s initial volume (100 ll) and dividing by the volume of the hemocytometer (0.1 ll). I was blind to the treatment when I counted sperm samples. I analyzed the effects of sperm competition treatment and male size class on 3 response variables: number of male mating attempts, the amount of sperm primed before mating trials, and the amount of sperm remaining in males after mating on day 10 (inverse measure of expenditure). Evans et al. (2003) found that, in the eastern mosquitofish, higher sperm expenditure does not always lead to higher sperm transfer to the female. They found that there was no difference between their treatment groups in terms of sperm transfer but that the groups differed with respect to sperm remaining in males after mating (i.e., some sperm may be lost from males but not actually transferred to the female’s gonoduct). In this experiment, as in Evans et al. (2003), sperm recovery from females was so low that I do not include it as a response variable (see also Robinson DM, Aspbury AS, Gabor CR, unpublished data). Comparison of the first treatment with the second and third treatments provides a test of the SCR model predictions (i.e., sperm production and expenditure should be higher in treatments 2 and 3 than in treatment 1), whereas comparison across the 3 treatments provides a test of the SCI model prediction (i.e., males in treatment 2 should expend greater amount of sperm than those in treatments 1 and 3). The data for number of mating attempts met assumptions of parametric tests without transformation. No transformations

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on the priming data led to equal variances between the groups, so I evaluated if there was an effect of male size class or treatment independently on sperm priming using Kruskal– Wallis tests. I used a square root transformation on the day 10 counts (the inverse of sperm expenditure) to meet assumptions of parametric tests. I fit a general linear model (GLM) to the number of mating attempts and to the transformed expenditure data. The main effects were sperm competition treatment and male size class. I also used sperm primed as a covariate and included the interaction between the main effects and between the main effects and the covariate. When significant differences in a response variable across categories were detected I used contrasts and/or multiple comparisons to test specific hypotheses. Based on Parker et al. (1996, 1997), the relevant comparisons are 1) risk model: between males with no risk (low sperm competition treatment) and males in the presence of risk (high and medium sperm competition treatment) and 2) intensity model: compare expenditure between low and medium treatments, compare expenditure between medium and high treatments, and compare expenditure between low and high treatments. Based on prior results (Aspbury and Gabor 2004), I expected that small males would expend more sperm than medium and large males, as they prime more sperm in the presence of females than do medium or large males (Aspbury and Gabor 2004). I used JMP 6.0 (copyright  2005 SAS Institute, Cary, NC) for all analyses. RESULTS There were no significant effects of sperm primed or any significant interactions on sperm expenditure or male mating attempts (all P . 0.21). Effects of sperm competition treatment There was a significant effect of sperm competition treatment on sperm priming (Kruskal–Wallis H ¼ 7.737; degrees of freedom [df] ¼ 2; P ¼ 0.021); male sailfin mollies primed more sperm before the mating trials in the high sperm competition treatment than in the low sperm competition treatment (Tukey–Kramer HSD test; Figure 1). There was no significant effect of sperm competition treatment on male mating attempts (GLM treatment effect test: v2 ¼ 4.11; df ¼ 2; P ¼ 0.128). There was a significant effect of sperm competition treatment on expenditure (Figure 2; GLM treatment effect test: v2 ¼ 9.97; df ¼ 2; P ¼ 0.007). To test predictions of the SCR model, I used contrasts to compare sperm expenditure between the low treatment (no risk) and the medium and high treatments (presence of risk). Male sailfin mollies in the high and medium treatments expended significantly more sperm than those males in the low treatment (contrast log likelihood ¼ 330.17; df ¼ 1; v2 ¼ 9.96; P ¼ 0.002), supporting predictions of the SCR model. To test the predictions of the SCI model, I compared all 3 treatments with one another using the Tukey–Kramer HSD test (Figure 2). There were significant differences between the low treatment and the medium treatment (difference ¼ 574.37), between the low treatment and the high treatment (difference ¼ 451.57), but not between the medium and high treatments (difference ¼ 122.80). Effects of male size There was no significant effect of male size class on sperm priming (Kruskal–Wallis H ¼ 1.549; df ¼ 2; P ¼ 0.461) or on male mating attempts (GLM male size effect test: v2 ¼ 3.02; df ¼ 2; P ¼ 0.221). However, there was a significant effect of male size class on sperm expenditure (GLM male size effect

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Figure 1 Box plots showing the sperm cells primed by male sailfin mollies (day 7–day 0) for 3 treatments of SCI (high ¼ 3 males, 1 females; medium ¼ 1 male, 3 females; low ¼ 0 males, 4 females). N ¼ 15 males per treatment. The line inside the box represents the median sperm cells primed. The lower and upper edges of the box represent the 25% and 75% of the distribution, respectively. The whiskers represent the outer 0% and 100% of the distribution. Lowercase letters indicate statistical differences based on Tukey–Kramer HSD test; treatments with no letters in common are statistically different at P ,0.05.

test: v2 ¼ 6.396; df ¼ 2; P ¼ 0.040). Small male sailfin mollies expended significantly more sperm than medium and large males (contrast log likelihood ¼ 328.45; df ¼ 1; v2 ¼ 4.161; P ¼ 0.041).

Figure 2 Mean 6 1 SE of the square root transformed number of sperm cells recovered from male sailfin mollies after mating in 3 treatments of sperm competition (high ¼ 3 males, 1 female; medium ¼ 1 male, 3 females; low ¼ 0 males, 4 females). N ¼ 15 males per treatment. Lower numbers indicate greater sperm expended during the mating trial. Lowercase letters indicate statistical differences based on Tukey–Kramer HSD test; treatments with no letters in common are statistically different at P ,0.05.

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Sperm competition in sailfin mollies

DISCUSSION The results of this study demonstrate that male sailfin mollies prime more sperm prior to mating and expend more sperm during mating in accordance with predictions of the SCR model of Parker et al. (1997). Males in the presence of competitors both primed more sperm prior to mating and expended more sperm than males in the absence of a male competitor. However, the results of this study suggest that male sailfin mollies do not adjust sperm priming or sperm expenditure in the manner predicted by the SCI model of Parker et al. (1996). Specifically, as the number of competitors increased from one (medium SCI) to 3 (high SCI), there was a difference neither in sperm priming nor in sperm expenditure, whereas the model of Parker et al. (1996) predicts sperm expenditure to be at the maximum when only one competing male is present. This pattern is not evident in the present data (Figures 1 and 2). This is the first study in a fish species with internal fertilization to demonstrate such a result and is consistent with studies in other species (e.g., Gage and Barnard 1996; Wedell and Cook 1999; Pizzari et al. 2003). However, support for the predictions of the SCI models has been found in other studies (insects: Simmons and Kvarnemo 1997; Schaus and Sakaluk 2001; subdominant birds: Pizzari et al. 2003; mammals: delBarco-Trillo and Ferkin 2006; and externally fertilizing fish: Candolin and Reynolds 2002; Pilastro et al. 2002; Smith et al. 2003). Two possible explanations for the results in the present study derive from how experiments testing SCI models are undertaken, as described by Engqvist and Reinhold (2005). First, Engqvist and Reinhold (2005) suggest that studies that use the presence of ‘‘audience’’ males (whose presence change the OSR) as a proxy of increasing SCI may underestimate the degree of SCI. In this study, males may have underestimated the SCI because the focal females in this study did not mate with the stimulus males. However, because male sailfin mollies mate in shoals, the probability that adjacent males either have had or will have the opportunity to mate with the focal female is high, in which case the presence of males should indicate an increase in SCI. Another ‘‘pitfall’’ in testing SCI models noted by Engqvist and Reinhold (2005) is that allocation patterns actually reflect prior male sperm production. In this study, however, I controlled for previous production by removing all sperm stores males held prior to the experiment and also measured the males’ sperm priming responses. Another possible interpretation of the results of this study is that the responses of the focal males were mediated by female behavior during the mating trial rather than the perceived risk (or intensity) of sperm competition. For example, female guppies can influence sperm transfer independent of male effects (Pilastro et al. 2004). It is also possible that females in this study were in different stages of their reproductive cycles or had different levels of stored sperm, and these variables could affect male responses. It is important to note that in this study, however, the females were haphazardly assigned to treatments, with all females showing no signs of gravidity. In addition, in the current study, there were no obvious differences in female behavior across the treatments (i.e., I did not note cases of overt female avoidance, such as staying on the bottom of the tank) during the mating trials. Although there are no studies that demonstrate that female behavior in poeciliids can influence male sperm priming or male sperm expenditure, this may be an interesting question to examine, given the evidence that females can influence the amount of sperm a male transfers to a female (Pilastro et al. 2004). As suggested by Parker (1998), as well as by authors of previous studies that have found either no pattern of sperm

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expenditure (Gryllus texensis: Schaus and Sakaluk 2001) or an increase in expenditure as SCI increases (Gage and Barnard 1996), the outcome of tests of SCI could reflect males occupying different roles. For example, in some species, males in a ‘‘sneak’’ role may have greater sperm expenditure than ‘‘guarder’’ males (Parker 1998). Sailfin mollies show variation in behavior and physiology with size (Farr et al. 1986; Travis and Woodward 1989; Aspbury and Gabor 2004). In this study, I found that small males expended the greatest amount of sperm, regardless of the number of competitors, than medium and large males. This result is in line with a previous study (Aspbury and Gabor 2004) that showed that smaller male sailfin mollies respond to social cues (presence or absence of females) by increasing sperm production to a much larger degree than do medium and large males. Therefore, selection acting differently on males of different size classes could lead to deviations from the predictions of the SCI model. By examining both sperm expenditure and sperm priming and controlling for the latter in a mating system with internal fertilization conducive to testing the predictions of Parker et al. (1996, 1997), I have been able to show that male sailfin mollies both prime and expend more sperm in the manner predicted by models of SCR (Parker et al. 1997). However, male sperm production and expenditure were not maximized with an intensity of one other competitor, which does not support the predictions of the SCI model (Parker et al. 1996). I thank Caitlin Gabor, members of the Texas State University Biology Department’s Ecology Evolution and Behavior discussion group, and 3 anonymous reviewers for critical comments on the manuscript. I also thank Holly Brewer, Kristen Epp, Celeste Espinedo, Rosie Gonzalez, Eric Holmes, and Donelle Robinson for assistance with fish maintenance. All experiments comply with the Animal Behavior Society Guidelines for the Use of Animals in Research and with the Animal Care Guidelines of Texas State University (Institutional Animal Care and Use Committee approval no. 39CGYe_01). This research was funded by National Science Foundation grant: DIB-0415808 to Caitlin R. Gabor and A.S.A.

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