Behavioral Ecology Advance Access originally published online on March 31, 2006
Behavioral Ecology 2006 17(4):581-585; doi:10.1093/beheco/ark001
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Male meadow voles respond differently to risk and intensity of sperm competition
Department of Biology, Ellington Hall, University of Memphis, Memphis, TN 38152, USA
Address correspondence to J. delBarco-Trillo. E-mail: jtrillo{at}memphis.edu.
Received 17 September 2005; revised 4 March 2006; accepted 9 March 2006.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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There are 2 models of male adjustment of sperm investment in the ejaculate in relation to sperm competition. The "risk model" predicts that as "risk" of sperm competition increases, sperm investment also increases. This prediction has been supported in many species, including mammals. The "intensity model" involves the number of competing males copulating with the same female and predicts that males will allocate the highest sperm investment at low sperm competition intensity (SCI) and then decreasing sperm investments as SCI increases. Two alternative outcomes are that sperm investment is unaffected by SCI and that sperm investment increases as SCI increases. There are studies supporting all 3 possible outcomes in relation to SCI but no data on mammals. The present paper presents the first study of SCI in a mammal species, the meadow vole, Microtus pennsylvanicus. We used odors of conspecific males to simulate low and high intensities of sperm competition. We found that males allocate the highest sperm investment at low SCI and decrease significantly their sperm investment at high SCI. We also found that males allocate the lowest sperm investment at low sperm competition risk (SCR) and the highest sperm investment at high SCR. All these results agree with current theoretical models of sperm competition.
Key words: ejaculation number, microtines, rodents, sperm counts, sperm investment.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Sperm competition takes place when the sperm of two or more males compete to fertilize the egg of the same female (Parker 1970
; Smith 1984; Birkhead and Møller 1998). Sperm competition is an important evolutionary force that has produced multiple male adaptations, both at the interspecific and intraspecific levels (Dixson and Anderson 2004; Ramm et al. 2005). For example, in those species in which sperm competition occurs frequently, males have larger testes (Harcourt et al., 1981, 1995; Birkhead and Møller 1998; Ramm et al. 2005), shorter and more muscular vas deferens (Anderson et al. 2004), and specialized sperm morphologies (Anderson and Dixson 2002; Moore et al. 2002). Behaviorally, males in species with high incidence of sperm competition show shorter ejaculation latencies, more ejaculations with the same female, and shorter interejaculatory intervals (Stockley and Preston 2004).
Many adaptations to sperm competition at the intraspecific level have also been reported (Birkhead and Møller 1998). Individual males in any species in which females mate promiscuously may modify their reproductive response depending on particular contexts, mainly adjusting their copulatory behavior and sperm investment (defined as the total number of sperm allocated by a male to a particular female). For example, intraspecific studies show that males exposed to a risk of sperm competition normally increase their frequency of copulations (Hogg 1988; Ginsberg and Rubenstein 1990) and reduce their latencies to copulate and their interejaculatory intervals (Busse and Estep 1984; Ginsberg and Rubenstein 1990; Lezama et al. 2001). Such changes in copulatory behavior are seen as adaptations that increase the number of sperm of a male in the sperm pool of a given female (Hogg 1988), displace the sperm of other males (Dewsbury 1981, 1985), or reduce female receptivity and thus sperm competition (Harcourt and Gardiner 1994; Stockley and Preston 2004). Although most of the examples offered here are mammal biased, adaptations to sperm competition are similarly abundant in other groups than mammals (Birkhead and Møller 1992, 1998; Simmons 2001).
The main prediction from the sperm competition theory is, indeed, that males will adjust their sperm investment in response to different sperm-competition contexts (Wedell et al. 2002). There are 2 main models that predict how males will adjust their sperm investment in response to sperm competition: the sperm competition risk (SCR) model and the sperm competition intensity (SCI) model (Parker et al. 1996, 1997; Parker 1998). The SCR model (Parker et al. 1997) involves 2 competing males. The risk of sperm competition is the probability that the ejaculate of 1 of the 2 males will compete against the ejaculate of the other male. A low risk of sperm competition implies that sperm competition will likely not occur, whereas a high risk of sperm competition implies that sperm competition will likely take place (Parker et al. 1997). The SCR model predicts a lower sperm investment when risk of sperm competition is low and a higher sperm investment when it increases (Parker et al. 1997). By doing so, a male may overcome the sperm of a competing male, thereby fertilizing more of the female's eggs (Lanier et al. 1979; Dewsbury 1984; Parker et al. 1997). Support for the SCR model has been documented in many groups of organisms (Gage 1991; Simmons and Kvarnemo 1997; Oppliger et al. 1998; Wedell and Cook 1999; Nicholls et al. 2001; Candolin and Reynolds 2002; Pilastro et al. 2002; Pizzari et al. 2003), including mammals (delBarco-Trillo and Ferkin 2004; Pound and Gage 2004).
The SCI model applies to species in which females may copulate with more than two males (Parker et al. 1996; Wedell et al. 2002). The "intensity" of sperm competition relates to the number of males competing for the same set of eggs. Consequently, under the SCI model, the occurrence of sperm competition is given, and thus SCR is assumed to be very high. The SCI model predicts that when SCI increases, a male should reduce his sperm investment (Parker et al. 1996; Wedell et al. 2002). The reason is that, as the number of competing ejaculates increases, the benefit of increasing sperm investment decreases (Parker et al. 1996). However, not all studies testing the SCI model support its predictions (Engqvist and Reinhold 2005). There are 3 potential ways in which males could respond to an increase in SCI. First, males may decrease their sperm investment when SCI increases, supporting the SCI model (Parker et al. 1996). Species that support this hypothesis are the bushcricket, Kawanaphila nartee (Simmons and Kvarnemo 1997), the cricket Gryllus veletis (Schaus and Sakaluk 2001), the bitterling, Rhodeus sericeus (Candolin and Reynolds 2002; Smith et al. 2003), subdominant males of the fowl, Gallus gallus (Pizzari et al. 2003), sneaker males of the grass goby, Zosterisessor ophiocephalus, and black goby, Gobius niger (Pilastro et al. 2002). Second, males may allocate higher sperm investments as SCI increases as reported in the small white butterfly, Pieris rapae (Wedell and Cook 1999), the house cricket, Acheta domesticus, and the decorated field cricket, Gryllodes supplicans (Gage and Barnard 1996). Third, males may allocate similar sperm investments independently of SCI as reported for the rainbow darter, Etheostoma caeruleum (Fuller 1998). Finally, males may not adjust sperm investment in relation to either SCR or SCI as reported for the crickets Gryllus texensis and Gryllodes sigillatus (Schaus and Sakaluk 2001) and 2 frog species (Byrne 2004).
Clearly, there is no single hypothesis that is best supported by available data on males' sperm investment in relation to high SCI. The fact that there is no general hypothesis may be due to differences in male adaptive responses to SCI or to methodological problems in manipulating male perception of SCI (Engqvist and Reinhold 2005). In any case, more studies with different species are necessary to better understand why different species may respond differently to high SCI. This is especially relevant in those animals, such as mammals, in which the SCI model is yet to be tested. Thus, the main goal of the present study was to test for the first time how mammals may respond to high SCI. To do so, we determined how meadow voles, Microtus pennsylvanicus, a promiscuous species (Boonstra et al. 1993) that is known to increase sperm investment in response to SCR (delBarco-Trillo and Ferkin 2004), respond to high SCI.
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METHODS |
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Animals
All meadow voles used in the study were second- and third-generation offspring of field-caught animals, born and raised in a temperature-controlled room with a 14:10 h light:dark cycle (lights on at 07:00 AM CST). This photoperiod simulates a day length typical of the breeding season. Tests were always run during the first 2 h of the light cycle. All meadow voles were weaned at 19 days of age, housed with littermates until 34 days of age, and then housed singly in clear polycarbonate cages (27 x 16.5 x 12.5 cm). Cages contained hardwood shavings as bedding and cotton as nesting material. Food (Formulab Diet 5008, PMI Nutrition International Inc., St Louis, Missouri) and tap water were provided ad libitum.
All animals were sexually mature and sexually experienced. Male and female average age was 208 and 200 days, respectively. All focal males were sexually rested and visually and olfactorily isolated from other individuals in the colony for at least 30 days before being used in this study. Wood partitions between cages and filter tops were used for visual and olfactory isolation, respectively. Females had previously produced at least one litter. However, females had not mated for 30 days prior to the start of the experiment. Consequently, no females were currently pregnant or lactating. We injected female voles with 0.05 mg estradiol benzoate 3 days before pairing with a male to increase the likelihood of the occurrence of mating (Dewsbury and Baumgardner 1981).
Experimental design
We used the same methodological paradigm, that is, odors of conspecific males, described elsewhere (delBarco-Trillo and Ferkin 2004), to simulate different intensities of sperm competition. We used 34 males and 34 females as focal animals. Odor donors were sexually mature males not used as focal males. Odor donors were genetically unrelated to their respective focal males. Procedures were as described in delBarco-Trillo and Ferkin (2004). Briefly, 20 g of treatment bedding (see below) was placed in a clean cage (37 x 21 x 15 cm) lined with clean bedding. An estradiol-primed female was introduced into the cage after the placement of the experimental bedding. The focal male was introduced in the cage 5 min later. Copulatory behavior was taped using a video camcorder connected to a VCR; we later scored the tape to determine the total number of ejaculations. If the female was not sexually receptive and copulatory behavior did not occur, that trial was discarded. All males were allowed to reach sexual satiety, previously established for meadow voles as 30 min without any copulation (Gray and Dewsbury 1975). After male sexual satiety, the female was anesthetized and then killed using an overdose of isoflurane. The female reproductive tract was removed, opened, and all the semen diluted in 25 ml of distilled water. The solution was gently homogenized and 4 sperm counts performed using an improved Neubauer hemacytometer. The average of the 4 sperm counts was used to estimate sperm investment. The sperm counter was blind to the treatment group.
There were 3 treatment groups: CONTROL, 1MB (1-male bedding), and 5MB (5-male bedding). The experimental bedding was the only differing variable between these 3 groups. In the CONTROL group, we used 20 g of bedding soaked in water. In the 1MB group, we used 20 g of soiled bedding taken from the cage of a conspecific male (odor donor). In the 5MB group, we used 4 g of soiled bedding from 5 odor donors. Thus, the total amount of bedding in the 5MB group was 20 g, as in the other 2 groups. The soiled bedding from each odor donor in the 5MB group was placed contiguously but without overlapping, and thus the area covered by the bedding in all groups was similar. The sample sizes for the CONTROL, 1MB, and 5MB were 12, 12, and 10, respectively. Because males with different body weights were randomly assigned to either group, the resulting average body weights were not significantly different (analysis of variance: F2,31 = 0.38, P = 0.69) in the CONTROL (mean ± SEM: 47.55 ± 2.21 g), 1MB (50.85 ± 2.84 g), and 5MB (49.4 ± 3.26 g) groups.
An important difference between the experimental design in the present study and the one reported by delBarco-Trillo and Ferkin (2004) is that we did not use a "within-animal" design in the present study. This was due to the difficulty of obtaining 3 successful trials with the same male. Generally, not using a within-animal design may be a problem in this type of study if there is much unexplained variation among males (Pound and Gage 2004). However, much of the variation in sperm investment among male meadow voles is explained by male body size (delBarco-Trillo and Ferkin 2004) and therefore may be controlled by incorporating male body size in the statistical analyses as a covariate.
Males were randomly assigned to their groups. Additionally, trials for each one of the 3 groups were alternated to avoid order effects.
Statistical analyses
Given that sperm investment is significantly correlated with male body weight (delBarco-Trillo and Ferkin 2004), we used analyses of covariance (ANCOVAs) to control for the effect of male body weight on sperm investment. The grouping variable was group (CONTROL, 1MB, and 5MB), and the covariate was male body weight. The Kolmogorov–Smirnov test was used to test the assumption of normality prior to running any ANCOVA. We log transformed any variable that did not meet the assumption of normality. Levene's homogeneity of variance test was used to test the assumption of homoscedasticity. We used ANCOVAs (the covariate being male body weight) with a Fisher's least significant difference adjustment for the pairwise comparisons (Day and Quinn 1989). If we used a different statistic test than ANCOVA, this is indicated. All statistic analyses were performed using SPSS 12.0 for Windows. Differences were considered significant at P < 0.05.
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RESULTS |
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We found significant differences in sperm investment between the 3 groups (ANCOVA: F2,30 = 13.5, P < 0.0005; Figure 1a,b). The lowest sperm investment was found in the CONTROL group (89.69 ± 10.84 x 106 sperm) and the highest sperm investment in the 1MB group (184.29 ± 17.03 x 106 sperm). Consequently, the difference in sperm investment between the CONTROL and 1MB groups was highly significant (F1,21 = 31.27, P < 0.0005). Sperm investment in the 5MB group (141.34 ± 15.83 x 106 sperm) was intermediate between the CONTROL group (CONTROL and 5MB pairwise comparison: F1,19 = 7.42, P = 0.013) and the 1MB group (1MB and 5MB pairwise comparison: F1,19 = 4.56, P = 0.046). Our data, therefore, support the hypothesis that male mammals may reduce their sperm investment as SCI increases (Parker et al. 1996
).
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As already reported by delBarco-Trillo and Ferkin (2004)
, we found a positive correlation between male body size and sperm investment (Pearson's correlation: r = 0.579, n = 34, P < 0.0005). We did not find any statistically significant differences in the number of ejaculations among the 3 groups (F2,30 = 2.002, P = 0.153), even though, in average, males in the CONTROL group performed one less ejaculation (mean ± SEM: 5.42 ± 0.31 ejaculations) than in the 1MB (6.5 ± 0.36 ejaculations) and the 5MB (6.6 ± 0.65 ejaculations) groups. We found no statistically significant differences for the pairwise comparisons between the CONTROL and 1MB groups (general linear model [GLM] with male body weight as covariate: F1,21 = 4.11, P = 0.056, effect size [Cohen's {1988} d] = 0.85), the CONTROL and 5MB groups (F1,19 = 2.72, P = 0.12, effect size = 0.71), and the 1MB and 5MB groups (F1,19 = 0.02, P = 0.89, effect size = 0.06). Because the number of ejaculations was relatively similar among groups, the number of sperm allocated per ejaculation differed among the 3 groups (F2,30 = 6.13, P = 0.006) in a way that parallels the results for total sperm investment. That is, number of sperm allocated per ejaculation was the lowest in the CONTROL group (18.18 ± 1.78 x 106 sperm per ejaculation), the highest in the 1MB group (29.76 ± 2.59 x 106 sperm per ejaculation), and intermediate in the 5MB group (22.67 ± 2.8 x 106 sperm per ejaculation). However, only the pairwise comparison between the CONTROL and 1MB groups was significantly different (GLM with male body weight as covariate: F1,19 = 12.03, P = 0.002).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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The present study is the first to investigate SCI in a mammal species. We found that male meadow voles allocate their highest sperm investment when risk of sperm competition is high but SCI is low and then significantly reduce their sperm investment when SCI increases (Figure 1). Overall, our results support the predictions of the SCI model (Parker et al. 1996
). That is, males should invest the most sperm when SCI is low and decrease their sperm expenditures as SCI increases (Parker et al. 1996). Several studies have also supported the SCI model (Simmons and Kvarnemo 1997; Schaus and Sakaluk 2001; Candolin and Reynolds 2002; Pilastro et al. 2002; Pizzari et al. 2003; Smith et al. 2003). However, 2 alternative outcomes have also been supported, namely that males allocate similar sperm investments independently of SCI (Fuller 1998) and that males allocate higher sperm investments as SCI increases (Gage and Barnard 1996; Wedell and Cook 1999). More studies with mammal species are needed to determine if mammals in general follow the SCI model or if different species respond differently to high SCI.
When testing SCI, there are some assumptions from the original models that should be carefully considered (Parker et al. 1996; Engqvist and Reinhold 2005). For example, the SCI model involves competing ejaculates (Parker et al. 1996). That is, the prediction of the model is that a male will adjust his sperm investment depending on the number of ejaculates already in competition. Engqvist and Reinhold (2005) suggested that researchers should modulate different intensities of sperm competition by using actual competing ejaculates, instead of indirect alternatives, such as presence of an audience of males or, as in the present study, cues from absent males. That is, the number of competing males involved in each group (e.g., 1 male or 5 males) should mate with a particular female before the focal male is allowed to mate with that female. Otherwise, focal males might underestimate the immediate SCI (Engqvist and Reinhold 2005). This may be true for some species but not necessarily for others; the best way to modulate experimentally SCI will rather depend on the ecological and behavioral characteristics of each particular species. For example, in species in which males spawn in groups (organisms for which the original SCI models were devised), males may actually be able to directly determine the approximate number of ejaculates competing for a set of eggs. However, what about solitary species with internal fertilization in which females mate sequentially with several males in the absence of any audience? Here, a focal male may be able to determine whether the female has mated or not, but he may not be able to estimate how many males have mated with that female. In such species, males may need to estimate SCI using proxy information, such as density of males in an area. Not considering such interspecific differences when testing the predictions of the SCI model may lead to erroneous conclusions. Consequently, for each particular species, researches should establish how males estimate SCI, and such information should be used to manipulate experimentally particular intensities of sperm competition. For example, the meadow vole is an asocial species during the breeding season (Ferkin 2001); males roam across diffuse and large territories that encompass several female territories, only associating with females during the duration of copulatory behavior. Thus, a male will not normally observe a female copulating with several other males before he copulates with her and will consequently need to estimate particular sperm competition intensities. Because meadow voles are asocial and their tallgrass environment impedes individuals from seeing afar, a male may not directly know how many other males are nearby. However, meadow voles scent mark profusely in prominent locations (Madison 1980; Ferkin et al. 2001). Consequently, it is likely that males get a clear idea of how many males may copulate with a particular female by detecting scent marks from other males in proximity to that female. Because female meadow voles are highly promiscuous (Boonstra et al. 1993; Berteaux et al. 1999), the number of sexually active males within a female's territory may be a good estimate of the number of males that will copulate with that female (i.e., SCI). This is why we consider that the 1MB group in the present study characterizes a context with low SCI, whereas the 5MB group characterizes a context with high SCI.
When using odors of conspecific individuals to simulate different sperm-competition contexts, there are at least 2 things to consider. First, it must be established that focal males can discriminate between the odors of conspecific males and the odors of any heterospecific males. Male meadow voles, for example, are able to differentiate between the odors of conspecific and heterospecific males (delBarco-Trillo and Ferkin 2004). Second, it must be established that males can discriminate between different quantities of odors (Ferkin et al. 2005). That is, if a male is exposed to odors of either 1 or 5 conspecific males, does that male experience the different number of odors as different? In meadow voles, there is data supporting the hypothesis that males can discriminate between different quantities of odors (Ferkin et al. 2005). Also, the fact that in the present study males responded differently in the 1MB and 5MB groups supports the hypothesis that male meadow voles are able to experience different quantities of odors as different.
We did not find statistically significant differences in the number of ejaculations among the CONTROL, 1MB and 5MB groups, even though, in average, males in the 1MB and 5MB groups performed one more ejaculation than males in the CONTROL group. However, it is not clear how such small difference in the number of ejaculations, by itself, might explain the large differences in sperm investment among the groups. Although we cannot rule out the possibility that male meadow voles modify their copulatory behavior to adjust at some degree their sperm investment, our data seem to indicate that changes in physiological parameters (such as contractility of the vas deferens or cauda epididymis) may be responsible for most part of the observed changes in sperm investment (Pound 1999; Anderson et al. 2004).
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ACKNOWLEDGEMENTS |
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We thank Anne Houde and 2 anonymous reviewers for comments on final versions of the manuscript. This work was supported by a Sigma Xi Grant-in-Aid of Research to J.d.-T., National Science Foundation Grant IOB 04553 to M.H.F., and National Institutes of Health Grant MH 61971 to M.H.F. and the Tennessee Mouse Genome Consortia. This research adhered to the Animal Behavior Society Guidelines for the Use of Animals in Research. All animal procedures were approved by the Institutional Animal Care and Use Committee of the University of Memphis.
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M. L Thomas and L. W Simmons Male-derived cuticular hydrocarbons signal sperm competition intensity and affect ejaculate expenditure in crickets Proc R Soc B, January 22, 2009; 276(1655): 383 - 388. [Abstract] [Full Text] [PDF]
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A. S. Aspbury Sperm competition effects on sperm production and expenditure in sailfin mollies, Poecilia latipinna Behav. Ecol., July 1, 2007; 18(4): 776 - 780. [Abstract] [Full Text] [PDF]
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S. A. Ramm and P. Stockley Ejaculate allocation under varying sperm competition risk in the house mouse, Mus musculus domesticus Behav. Ecol., March 1, 2007; 18(2): 491 - 495. [Abstract] [Full Text] [PDF]
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L. Engqvist and K. Reinhold Sperm competition games: optimal sperm allocation in response to the size of competing ejaculates Proc R Soc B, January 22, 2007; 274(1607): 209 - 217. [Abstract] [Full Text] [PDF]
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