doi: 10.1111/j.1420-9101.2011.02293.x Adjustment of sperm allocation under high risk of sperm competition across taxa: a meta-analysis J. D E L BARCO-TRILLO Department of Evolutionary Anthropology, Duke University, Durham, NC, USA Keywords: Abstract meta-analysis; number of offspring; phylogeny; sperm allocation; sperm competition; sperm investment. Sperm competition theory predicts that under high risk of sperm competition, males will increase the number of sperm that they allocate to a female. This prediction has been supported by some experimental studies but not by others. Here, I conducted a meta-analysis to determine whether the increase in sperm allocation under high risk of sperm competition is a generalized response across taxa. I collected data from 39 studies and 37 species. Across taxa, males under a high risk of sperm competition respond by increasing their sperm allocation (mean effect size = 0.32). Number of offspring did not explain a significant portion of the variation in effect sizes. A traditional meta-analysis (i.e. without phylogenetic information) described the variation among effect sizes better than a meta-analysis that incorporates the phylogenetic relationships among species, suggesting that the increase in sperm allocation under high risk of sperm competition is similarly prevalent across taxa. Introduction Sperm competition is an important component of sexual selection that occurs when two or more males mate with a particular female during the same reproductive cycle, and their sperm compete to fertilize the female’s available eggs (Parker, 1970; Birkhead & Møller, 1998). Sperm competition is prevalent in most taxa. For example, more than 95% of mammalian species are estimated to experience sperm competition (Kleiman, 1977). The frequent occurrence of sperm competition may have forced males to develop different strategies to overcome the sperm of competing males (Parker, 1984, 1990a). One strategy for overcoming the sperm of other males involves adjusting the number of sperm allocated into the ejaculate (Parker, 1998; Wedell et al., 2002; Parker & Pizzari, 2010). The facultative adjustment of sperm allocation (defined as the total number of sperm allocated by a male to a particular female) is a consequence of sperm production being costly to males (Dewsbury, 1982). Correspondence: Javier delBarco-Trillo, Department of Evolutionary Anthropology, Duke University, 128 Biological Sciences Building, Box 90383, Durham, NC 27708, USA. Tel.: 919 660 7364; fax: 919 660 7348; e-mail: delbarcotrillo@gmail.com 1706 There are two main models that predict how males will adjust their sperm allocation in response to sperm competition: the risk and the intensity models (Parker et al., 1996, 1997; Parker, 1998; Parker & Pizzari, 2010). The sperm competition risk model involves two competing males (Parker et al., 1997). The ‘risk’ is the probability that the ejaculate of one of the two males will compete against the ejaculate of the other male. A low risk implies that sperm competition will likely not take place, whereas a high risk implies that sperm competition will likely occur (Parker et al., 1997). The sperm competition risk model predicts a lower sperm allocation when the risk of sperm competition is low and a higher sperm allocation when the risk is high (Parker et al., 1997). By increasing his sperm allocation under a high risk of sperm competition, a male can overcome the sperm of a competing male, thereby fertilizing more of the female’s eggs (Dewsbury, 1984; Parker et al., 1997). The sperm competition intensity model applies when females can mate with more than two males (Parker et al., 1996; Wedell et al., 2002). The ‘intensity’ refers to the number of males competing for the same set of eggs. In this model, the occurrence of sperm competition is given, and thus, the risk of sperm competition is assumed to be high. The intensity model predicts that as the intensity increases, a male should reduce his sperm allocation ª 2011 THE AUTHOR. J. EVOL. BIOL. 24 (2011) 1706–1714 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2011 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY Meta-analysis of sperm allocation (Parker et al., 1996; Wedell et al., 2002) because as the number of competing ejaculates increases, the benefit accrued by increasing sperm allocation decreases (Parker et al., 1996). Even though the risk and intensity models have been treated separately, more recent models combine the entire range from low risk to high intensity (Parker & Pizzari, 2010). The prediction that males will ejaculate a greater number of sperm under high risk of sperm competition than under low risk of sperm competition (Parker, 1990a,b; Parker et al., 1996) has been supported by experimental studies in several species encompassing a wide range of taxa, including annelids (Velando et al., 2008), insects (Gage, 1991), fish (Pilastro et al., 2002), birds (Pizzari et al., 2003) and mammals (delBarco-Trillo & Ferkin, 2004). However, other studies did not find a significant increase in sperm allocation in response to high risk of sperm competition (Locher & Baur, 2000; Byrne, 2004; Ramm & Stockley, 2007). As a consequence, it is not clear whether the increase in sperm allocation in relation to high risk of sperm competition is a generalized response across taxa. Taking advantage of the abundant literature on sperm allocation under low and high risks of sperm competition, I conducted metaanalyses to determine whether the literature supports the prediction that males increase their sperm allocation under high risk of sperm competition. A meta-analysis is a quantitative approach that synthesizes a set of independent studies addressing the same question (Borenstein et al., 2009). Briefly, an effect size is calculated for each individual study. In this case, the effect size would be a measure of the increase in sperm allocation under a high risk of sperm competition context compared with the sperm allocation under a low risk of sperm competition context. A meta-analysis combines all those effect sizes into an estimate of the overall strength of the effect (i.e. the increase in sperm allocation under high risk of sperm competition) to determine whether the overall effect size is statistically significant. I conducted a meta-analysis that incorporates the phylogenetic relationships among species and a traditional meta-analysis (i.e. without phylogenetic information) and compared both to determine whether the increase in sperm allocation under high risk of sperm competition differs among taxonomic groups or sections of a phylogenetic tree (Lajeunesse, 2009). That is, if there are taxonomic groups in which the response is generally higher than in other taxonomic groups, the phylogenetic meta-analysis will fit the data better than the traditional meta-analysis. For example, taxonomic variance in the response could be due to different sensory abilities among groups to detect variations in the risk of sperm competition or to the differential ability of the male reproductive tract in different groups to control the number of sperm in the ejaculate. Additionally, given the large variation in the average number of offspring produced by the different species 1707 included in the meta-analysis, I tested whether the effect sizes correlated with the number of offspring, by including the number of offspring as a covariate in the metaanalysis. Everything else being equal, sperm competition for each egg will be more intense when there are fewer eggs to be fertilized (Reinhold et al., 2002). When a female produces many eggs, each male competitor will likely fertilize a proportion of those eggs regardless of the sperm allocation from each male; however, in the extreme case in which a female produces only one egg, only one male will fertilize that egg, so it would pay more to increase sperm allocation when rival males are also trying to fertilize that egg. Consequently, I predicted that in species in which females produce fewer eggs, males will show a higher increase in sperm allocation under high risk of sperm competition. Materials and methods I made a comprehensive search of the literature in Web of Science using a combination of terms (e.g. [sperm OR ejaculate] AND [competition OR allocation OR investment OR count OR number OR output OR production OR economy OR expenditure OR adjustment]). I selected studies in which sperm allocation was measured under two contexts characterizing both low and high risks of sperm competition. Given that risk and intensity of sperm competition lead to different predictions about sperm allocation, if a study included risk and intensity treatments, I selected the treatment that best approximated a high risk but a low intensity of sperm competition. That is, if subject males were exposed for instance to one competitor or several competitors during mating, I selected the one-competitor treatment as the high risk of sperm competition context. I only considered studies in which males copulated with a female, and the ejaculated sperm was measured. That is, I did not select studies in which sperm was extracted from males, because I was not interested in the number of sperm that a male had but in the number of sperm that a male would ejaculate under low and high risks of sperm competition. I collected data from 39 studies and 37 species, including one mollusc, one annelid, 18 insects (nine of which were orthopterans), three crustaceans, seven fish, one amphibian, two birds and four mammals (Table 1). When studies reported both the number of apyrene (nonfertile) sperm and eupyrene (fertilizing) sperm, I used only the values for eupyrene sperm. I calculated Hedge’s d as a measure of effect size for each study (Rosenberg et al., 2000). Hedge’s d incorporates the sample size, the mean and the standard deviation of the two treatments (i.e. sperm allocation under low and high risks of sperm competition). Hedge’s d is an appropriate effect size when dealing with studies with small sample sizes (Rosenberg et al., 2000). An effect size close to zero indicates that males invest similar numbers of sperm under low and high risks of sperm ª 2011 THE AUTHOR. J. EVOL. BIOL. 24 (2011) 1706–1714 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2011 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY 1708 Table 1 Species considered in the meta-analyses, summary of the original data, calculated Hedge’s d and variance, and average offspring of each species. N N ª 2011 THE AUTHOR. J. EVOL. BIOL. 24 (2011) 1706–1714 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2011 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY Species Measure Ref. Acanthoplus discoidalis Arianta arbustorum Arianta arbustorum Austropotamobius italicus Callinectes sapidus Sperm # Sperm # 103 sperm Area covered (cm2) Estimated % of available ejaculate Sperm # Sperm # Ejaculate volume (mm3) 106 sperm 107 sperm Ampulla size (mg) Ejaculate volume (mm3) Sperm # Relative sperm investment* 106 sperm 4 · 104 sperm ⁄ ll Ejaculate size 106 sperm Sperm # ⁄ ml Log sperm # ⁄ ml Sperm # ⁄ 10 ll Sperm # ⁄ 10 ll Sperm # ⁄ 10 ll 105 sperm 105 sperm 106 sperm Log 106 sperm 106 sperm Volume of packed sperm 109 sperm Sperm # Ejaculate weight (mg) Sperm # Sperm # 300 · sperm # ⁄ male weight 1 2 3 4 5 a a b a b 14 55 18 30 40 253 000 2 143 157 1701 0.34 57.92 32 501.91 657 853.89 623.67 0.11 11.60 13 36 18 30 53 239 666.7 2 249 285 1655 0.36 65.53 6 7 8 9 10 11 12 13 14 b b b a b a a b b 50 20 10 16 34 31 14 25 4 2249.3 1379 103.04 0.58 1.88 551 0.13 12 900 000 0.46 7212.49 1078 15.46 0.32 2.19 89.08 0.07 6 250 000 0.16 50 20 10 12 40 57 14 24 8 15 16 17 18 19 20 21 21 21 22 23 24 25 26 27 b b b b b b b b b b a b b b b 31 5 21 17 5 21 24 24 24 10 43 10 13 6 14 0.03 2.64 1.28 11.28 172.9 3.59 152.15 110.28 145.66 5.61 24.8 98.12 2.18 4.38 92.1 1.06 2.03 0.89 6.89 35.55 0.93 85.5 59.9 88.3 0.81 15.08 56.32 0.44 2.18 113.37 28 29 30 31 32 33 b b b a,bà b b 9 4 11 26 18 16 0.9 38.76 1.33 3942 3267 29 600 Callosobruchus chinensis Ceratitis capitata Cimex lectularius Coptaspis sp. 2 Crinia georgiana Decticus verrucivorus Eisenia andrei Etheostoma caeruleum Gallus gallus Gambusia holbrooki Gampsocleis gratiosa Gasterosteus aculeatus Gasterosteus aculeatus Gobius niger Gobius niger Gryllodes sigillatus Gryllus texensis Gryllus veletis Hapalogaster dentata Helicoverpa armigera Microtus pennsylvanicus Mus musculus domesticus Mus musculus domesticus Oncorhynchus mykiss Ovis aries Phyllomorpha laciniata Pieris napi Plodia interpunctella Plodia interpunctella Pseudaletia separata Mean§ SD 2.1 54 7.8 10 279 5930 20 600 Hedge’s d Var d Average offspring Ref. 27 273.1 919 728 844.29 0.11 13.83 -0.4295 0.1364 -0.0606 0.1803 0.5839 0.15 0.05 0.11 0.07 0.05 60 103.3 103.3 96.7 3 000 000 40 3 3 41 42 2288 3520 59.02 0.86 2.04 458 0.38 21 670 000 0.74 9415.83 1865 11.35 0.27 2.00 90.60 0.22 15 578 755 0.16 0.0046 1.3777 -3.1081 0.9004 0.0759 -1.0235 1.4495 0.7327 1.6432 0.04 0.12 0.44 0.16 0.05 0.06 0.18 0.09 0.49 75 246.4 294.35 60 65.81 42.6 6 8 10 43 44 45 40 46 11 47 48 49 25 5 21 17 5 21 24 24 24 8 19 10 13 6 14 0.03 3.02 1.57 18.54 210 3.40 160.25 119.38 184.75 7.02 34.6 168.99 1.84 5.29 87.5 0.6 3.62 1.10 14.06 47.40 1.85 46.8 70.8 110.5 1.31 10.90 57.30 0.38 2.69 101.02 0 0.1168 0.2793 0.6403 0.7998 -0.122 0.1156 0.1365 0.3844 1.2731 0.6932 1.1947 -0.7983 0.3428 -0.0416 0.07 0.40 0.10 0.12 0.43 0.10 0.08 0.08 0.08 0.27 0.08 0.24 0.17 0.34 0.14 36 42.6 112 112 13 339 13 339 438 541 14.34 1000 876 5.51 5.2 5.2 3500 50 40 51 51 52 52 53 54 53 55 56 57 58 58 59 9 3 10 33 24 14 3.5 856.33 9.3 10 566 9050 20 100 1.2 1185.92 1.26 3487 4409 36 294 1.2571 0.9001 1.1096 0.0767 0.7722 -0.0148 0.27 0.64 0.22 0.07 0.10 0.13 1 2 245.1 319 319 1668 40 60 61 62 62 63 Mean§ SD DELBARCO-TRILLO High risk of sperm competition J. Low risk of sperm competition Conveyed risks Species Measure Ref. Conveyed risks Rattus norvegicus Requena verticalis Rhodeus amarus Riparia riparia Teleogryllus oceanicus Tenebrio molitor Zosterisessor ophiocephalus Zosterisessor ophiocephalus 106 sperm 103 sperm 104 sperm 106 sperm 103 sperm Sperm # Sperm # ⁄ ml Log sperm # ⁄ ml 34 35 36 37 38 39 19 20 b a b b a b b b Low risk of sperm competition High risk of sperm competition N Mean§ SD N Mean§ SD Hedge’s d Var d Average offspring Ref. 12 17 13 315 44 39 8 12 79.6 773.2 13.22 2.7 78.23 8774 162.4 6.02 52.65 558.68 12.96 2.23 20.36 6988 84.85 2.70 12 12 13 138 44 45 8 12 118.3 834.7 10.98 3.14 75.46 17 665 240 6.30 86.26 405.65 5.38 2.38 19.17 10 398 169.71 2.00 0.5229 0.1191 -0.2184 0.1929 -0.1384 0.981 0.5468 0.1134 0.17 0.14 0.15 0.01 0.05 0.05 0.26 0.17 10.84 43 3 3.6 160 12.25 27 500 27 500 64 65 66 67 68 69 70 70 *Values are for dominant males. The ways in which the low and high risks of sperm competition were conveyed are, respectively: a, virgin vs. nonvirgin female; b, absence vs. presence of competitor male or his cues. àThe data presented and used are for the experimental design involving the absence vs. presence of a competitor male. §The mean refers to the measure given in the ‘Measure’ column. References: 1, (Bateman & Ferguson, 2004); 2, (Baur et al., 1998); 3, (Locher & Baur, 2000); 4, (Galeotti et al., 2007); 5, (Jivoff, 1997); 6, (Yamane & Miyatake, 2005); 7, (Gage, 1991); 8, (Siva-Jothy & Stutt, 2003); 9, (Wedell, 1998); 10, (Byrne, 2004); 11, (Wedell, 1992); 12, (Velando et al., 2008); 13, (Fuller, 1998); 14, (Pizzari et al., 2003); 15, (Evans et al., 2003); 16, (Gao & Kang, 2006); 17, (Zbinden et al., 2004); 18, (Zbinden et al., 2003); 19, (Pilastro et al., 2002); 20, (Scaggiante et al., 2005); 21, (Schaus & Sakaluk, 2001); 22, (Sato & Goshima, 2007); 23, (Teng & Zhang, 2009); 24, (delBarco-Trillo & Ferkin, 2004); 25, (Ramm & Stockley, 2007); 26, (Ramm & Stockley, 2009); 27, (Fitzpatrick & Liley, 2008); 28, (Lezama et al., 2001); 29, (Garcı́a-González & Gomendio, 2004); 30, (Larsdotter Mellström & Wiklund, 2009); 31, (Cook & Gage, 1995); 32, (Gage, 1995); 33, (He & Miyata, 1997); 34, (Pound & Gage, 2004); 35, (Simmons et al., 1993); 36, (Smith et al., 2009); 37, (Nicholls et al., 2001); 38, (Thomas & Simmons, 2007); 39, (Gage & Baker, 1991); 40, estimated value based on similar species; 41, (Galeotti et al., 2006); 42, (Hines et al., 2003); 43, (Yanagi & Miyatake, 2003); 44, (McDonald & McInnis, 1985); 45, (Stutt & Siva-Jothy, 2001); 46, (Byrne & Roberts, 1999); 47, (Domı́nguez et al., 2000); 48, (Fuller, 1985); 49, (Parker, 2003); 50, (Vargas & Sostoa, 1996); 51, (Wallace & Selman, 1979); 52, (Mazzoldi & Rasotto, 2002); 53, (Burpee & Sakaluk, 1993); 54, (Shoemaker et al., 2006); 55, (Sato & Goshima, 2006); 56, (Hou & Sheng, 1999); 57, (delBarco-Trillo & Ferkin, 2006b); 58, (Krackow, 1992); 59, http://genomics.senescence.info/ species/entry.php?species=Oncorhynchus_mykiss; 60, (Reguera & Gomendio, 2002); 61, (Wiklund et al., 1993); 62, (Arbogast, 1981); 63, (Kanda & Oya, 1985); 64, (Dollinger et al., 1980); 65, (Gwynne, 1988); 66, (Mills & Reynolds, 2002); 67, (Moreno & Carlson, 1989); 68, (Simmons et al., 2006); 69, (Drnevich et al., 2001); 70, http://species-identification.org/ species.php?species_group=fnam&id=1663. Meta-analysis of sperm allocation ª 2011 THE AUTHOR. J. EVOL. BIOL. 24 (2011) 1706–1714 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2011 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY Table 1 (Continued) 1709 1710 J. DELBARCO-TRILLO competition. A negative effect size indicates a higher sperm allocation under low risk of sperm competition, whereas a positive effect size indicates a higher sperm allocation under high risk of sperm competition. Meta-analyses have not traditionally incorporated information about the phylogenetic relationships among the different species under consideration. Several recent studies, however, have developed approaches to incorporate phylogenetic information in meta-analyses (Adams, 2008; Lajeunesse, 2009; Hadfield & Nakagawa, 2010). To determine whether the magnitude of the effect sizes could be explained by phylogenetic factors (Lajeunesse, 2009), I used Phylometa 1.0 (lajeunesse.nescent. org ⁄ software.html). Phylometa offers a comparison between the fit of a traditional meta-analysis (i.e. without the incorporation of phylogenetic relationships among taxa) versus a phylogenetically independent meta-analysis (Lajeunesse, 2009). Consequently, one can decide which model (including or not phylogenetic information) best describes variation among effect sizes (Lajeunesse, 2009). I used several sources to construct the phylogeny of the 37 species included in the meta-analysis (see Data S1). I set all branch lengths equal to 1 and used the random effect model in Phylometa. I ran separate metaanalyses in which I separated the studies by the type of methodological approach used to convey low and high risks of sperm competition. Studies conveyed low and high risks of sperm competition in two different ways (Table 1): In some studies, males were paired with a virgin (low risk) or a nonvirgin female (high risk), whereas in other studies, males were paired with a female in the absence of a competitor or his cues (low risk) or in the presence of a competitor or his cues (high risk). After finding in Phylometa that a traditional metaanalysis was a better fit for the data, I used MetaWin 2.1.5.10 (Rosenberg et al., 2000) to conduct a traditional meta-analysis including the average number of offspring in a reproductive bout as a covariate. The average number of offspring for each species is included in Table 1 and refers to the number of offspring that a male might father after mating with a female in one reproductive bout. I log10-transformed each average number of offspring. I used the random and continuous model in MetaWin. It must be noted that the inclusion of number of offspring as a covariate was prior to determining that heterogeneity was not statistically significant. Significant heterogeneity among studies indicates that the variance among effect sizes is greater than expected by sampling error and that other explanatory variables should be investigated (Cooper, 1998; Rosenberg et al., 2000). cies, males increase their sperm allocation when there is a high risk of sperm competition; this overall increase was statistically significant in the traditional meta-analysis (mean effect size = 0.315; variance = 0.01; 95% CI = 0.122–0.509; Z1 = 10.19, P = 0.0014), but not in the phylogenetically independent meta-analysis (mean effect size = 0.301; variance = 0.03; 95% CI = )0.037 to 0.638; Z1 = 3.05, P = 0.08). The type of experimental design used to convey low and high risks of sperm competition (Table 1) leads to different results. In studies in which subject males mated with a virgin (low risk) or a nonvirgin (high risk) female, there was not a significant overall increase in sperm allocation under high risk of sperm competition; this was the case both in a traditional meta-analysis (mean effect size = 0.152; variance = 0.034; 95% CI = )0.209–0.512; Z1 = 0.68, P = 0.41) and in a phylogenetically independent meta-analysis (mean effect size = )0.063; variance = 0.028; 95% CI = )0.392–0.265; Z1 = 0.14, P = 0.71). Contrarily, in studies in which subject males mated with a female in the absence (low risk) or the presence (high risk) of a competitor male or his cues, there was a significant overall increase in sperm allocation under high risk of sperm competition, both in a traditional meta-analysis (mean effect size = 0.335; variance = 0.01; 95% CI = 0.135–0.534; Z1 = 10.77, P = 0.001) and in a phylogenetically independent meta-analysis (mean effect size = 0.282; variance = 0.02; 95% CI = 0.043–0.52; Z1 = 5.35, P = 0.021). Using MetaWin and including the number of offspring as a covariate, the mean effect size was 0.29, which was significantly different from zero (95% CI = 0.11–0.48). The number of offspring did not explain a significant portion of the variation in effect sizes (slope = )0.03, P = 0.72; Fig. 1). In fact, there was not significant heterogeneity (Qtotal42 = 54.6, P = 0.09). That is, the set of effect sizes are homogeneous, and the addition of explanatory variables in the model is unlikely to show significant differences among groups of species. The estimated number of additional studies with an effect size of zero required to make the mean effect size nonsignificant was 456 (Rosenthal’s method), indicating that the results are unlikely to be affected by publication bias. It must be noted, however, that the Rosenthal’s method excludes the possibility of unpublished studies with negative effect sizes (Palmer, 1999). A funnel plot between effect sizes and sample sizes did not show any apparent publication bias (Fig. 2). Removing the study with the largest sample size still resulted in a significant increase in sperm allocation under high risk of sperm competition (mean effect size = 0.3; 95% CI = 0.1–0.5). Results The first analysis in Phylometa showed that a traditional meta-analysis was a better fit for the data (AIC, Akaike’s information criterion = 117.96) than a phylogenetically independent meta-analysis (AIC = 162.81). Across spe- Discussion Across taxa ranging from annelids to mammals, males under a high risk of sperm competition respond by increasing their sperm allocation, supporting a major ª 2011 THE AUTHOR. J. EVOL. BIOL. 24 (2011) 1706–1714 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2011 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY Meta-analysis of sperm allocation Fig. 1 No relationship between effect sizes (a measure of the increase in sperm allocation under high risk of sperm competition) and number of offspring. The dashed line indicates species with positive effect sizes (over the line) and species with negative effect sizes (below the line). Fig. 2 Funnel plot showing the relationship between effect sizes and combined sample size. Each combined sample size was calculated by adding the sample sizes of the low and high risk groups. The dashed line indicates the overall mean effect size. prediction of sperm competition theory (Parker, 1990a,b; Parker et al., 1996). The increase in sperm allocation under high risk of sperm competition is not more pronounced in some taxonomic groups than in others, or in any particular portion of the phylogeny. Instead, there is a similar response across species independent of their phylogenetic relationships. This points out to the importance and prevalence of this response across taxa and makes unlikely the existence of morphological or physiological constraints that may prevent the expression of such a response in some taxonomic groups. Very recently, Kelly & Jennions (2011) have also conducted meta-analyses to determine whether males adjust their sperm allocation depending on the risk of 1711 sperm competition. I acknowledged this other study after the completion of my study, so both studies are independent assessments of the same topic. Even though the two studies used different datasets, the results in both studies are similar. Most importantly, both studies showed that sperm allocation increases when the risk of sperm competition increases. In addition, using different approaches, both studies showed a lack of significant publication bias on the sperm allocation literature. How low and high risks of sperm competition are experimentally conveyed to subject males can influence male response. Studies on sperm allocation under different levels of sperm competition have used two alternative methodological approaches. Whereas some studies paired the subject males with either a virgin or a nonvirgin female, other studies paired the subject males either in the absence or in the presence of a competitor male or his cues. An interesting difference between these two approaches is that in the nonvirgin context, the female has already mated, whereas in the male-presence context, the female may be likely to mate with the other male but she has not done so yet. Males may experience these two contexts differently (Engqvist & Reinhold, 2005; Parker & Pizzari, 2010). Nevertheless, assuming that males in all species studied can correctly determine the mating status of a female, the risk of sperm competition can be considered to be as high or higher in the nonvirgin context compared with the male-presence context. However, I found an overall increase in sperm allocation in the male-presence context (relative to the male-absence context), but not in the nonvirgin context (relative to the virgin context). In their separate meta-analyses, Kelly & Jennions (2011), when using direct measures of sperm allocation, also found that males increase their sperm allocation in the presence of competitors but not depending on the mating status of the female. These results suggest that males may be more stimulated by the presence of competitors around the time of mating than by the cues of previous mating by the female. The lack of heterogeneity in the effect sizes indicates that the variance among effect sizes can be simply explained by sampling error. Thus, it does not seem that any factor or covariate could differentiate two or more groups of species on how males adjust their sperm allocation in response to high risk of sperm competition. For example, there was not a relationship between effect sizes and the average number of offspring. In some species, especially those that produce a great number of eggs, males may allocate more sperm with increasing clutch sizes (Shapiro et al., 1994; Marconato & Shapiro, 1996). However, the present study suggests that the increase in sperm allocation under a high risk of sperm competition from a baseline sperm allocation (i.e. when risk of sperm competition is low) is independent of the average number of eggs produced by females. The present meta-analysis was possible due to the relatively large number of studies measuring sperm ª 2011 THE AUTHOR. J. EVOL. BIOL. 24 (2011) 1706–1714 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2011 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY 1712 J. DELBARCO-TRILLO allocation under low and high risks of sperm competition. In contrast, the number of studies measuring sperm allocation under low and high intensities of sperm competition is still relatively low (Byrne, 2004; delBarcoTrillo & Ferkin, 2006a). However, it would be interesting to determine whether there is an overall response to different intensities of sperm competition across studies and species. This may not be the case, as there are different predictions about how males should respond to high intensity relative to low intensity depending on several factors, such as the average level of sperm competition in the population or species, how much information a male has about the level of sperm competition, the mechanism of sperm competition (e.g. fair raffle, loaded raffle, direct sperm displacement, stratification) and how much an increase in sperm numbers affects fertilization rates (Parker & Pizzari, 2010). Despite the low number of studies available, Kelly & Jennions (2011) conducted a meta-analysis on these studies and found no significant effect of the number of rivals (i.e. different levels of intensity of sperm competition) on sperm allocation. In this study, I only considered sperm numbers. However, males in a context with high risk of sperm competition could also adjust their ejaculates by changing sperm traits, such as sperm viability or motility (Snook, 2005; Thomas & Simmons, 2007). These changes may be due, for example, to the differential incorporation of seminal substances depending on the sperm competition context (Thomas & Simmons, 2007). Males can also manipulate egg production or female receptivity depending on the level of sperm competition by altering seminal substances; for instance, Drosophila melanogaster males allocate more seminal fluid proteins (sex peptide and ovulin) to females under high risk of sperm competition than under low risk of sperm competition (Wigby et al., 2009). When more studies accumulate on rapid adjustment of sperm traits or seminal components under different risks of sperm competition, it will be possible not only to determine whether there is an overall response across taxa but also to compare the relative importance of adjustments in sperm numbers, sperm traits and seminal components. Acknowledgments I am grateful to Matt Gage, Rhonda Snook, Tom Pizzari and an anonymous reviewer for helpful comments on the manuscript. References Adams, D.C. 2008. Phylogenetic meta-analysis. Evolution 62: 567–572. Arbogast, R.T. 1981. Mortality and reproduction of Ephestia cautella and Plodia interpunctella exposed as pupae to high temperatures. Environ. Entomol. 10: 708–714. delBarco-Trillo, J. & Ferkin, M.H. 2004. Male mammals respond to a risk of sperm competition conveyed by odours of conspecific males. Nature 431: 446–449. delBarco-Trillo, J. & Ferkin, M.H. 2006a. Male meadow voles respond differently to risk and intensity of sperm competition. 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Supporting information Additional Supporting Information may be found in the online version of this article: Data S1 Electronic supplementary material 1. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer-reviewed and may be reorganized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Received 12 November 2010; revised 11 April 2011; accepted 14 April 2011 ª 2011 THE AUTHOR. J. EVOL. BIOL. 24 (2011) 1706–1714 JOURNAL OF EVOLUTIONARY BIOLOGY ª 2011 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY