Gamelon

Marlène Gamelon
email: marlene.gamelon@univ-lyon1.fr

Jean-Michel Gaillard

Eric Baubet

Sébastien Devillard

Ludovic Say

Serge Brandt

Olivier Gimenez

The relationship between phenotypic variation among offspring and mother body mass in wild boar: Evidence of coin-flipping?

Keywords: bet-hedging, phenotypic plasticity, repeatability, reproductive tactic, Sus scrofa scrofa bet-hedging, phenotypic plasticity, repeatability, reproductive tactic, Sus scrofa scrofa -9.183713 13

1. In highly variable environments, the optimal reproductive tactics of iteroparous organisms should minimize variance in yearly reproductive success to maximize the long-term average reproductive success. To minimize among-year variation in reproductive success individuals can either minimize the variance in the number of offspring produced at each reproductive attempt (classical bet-hedging) or maximize the phenotypic diversity of offspring produced within or among reproductive attempts (coin-flipping).

2. From a long-term detailed study of an intensively exploited population facing a highly unpredictable environment, we identify a continuum of reproductive tactics in wild boar females depending on their body mass.

3.

At one end, light females adjusted litter size to their body mass and produced highly similar-sized offspring within a litter. These females fitted the hypothesis of individual optimization commonly reported in warm-blooded species, which involves both an optimal mass and an optimal number of offspring for a given mother. At the other end of the continuum, heavy females produced litters of variable size including a mixture of heavy and light offspring within litters.

4.

Prolific heavy wild boar females diversify the phenotype of their offspring, providing a first evidence for coin-flipping in a warm-blooded species.

Introduction Bet-hedging (Murphy 1968, Slatkin 1974) refers to the way organisms increase their fitness by decreasing the variance of annual reproductive success [START_REF] Philippi | Hedging one's evolutionary bets, revisited[END_REF]. In unpredictable and variable environments, the life history tactic leading to the highest individual fitness involves minimizing among-year variation in reproductive success rather than consistently maximizing reproductive success each year (Slatkin 1974;[START_REF] Philippi | Hedging one's evolutionary bets, revisited[END_REF]). Bet-hedging includes two non-exclusive mechanisms, risk spreading and riskminimizing [START_REF] Seger | What is bet-hedging?[END_REF]. For instance, iteroparity corresponds to a riskspreading tactic, which has been interpreted as a response to environmental variation [START_REF] Charnov | Life-History consequences of natural selection: Cole's result revisited[END_REF][START_REF] Schaffer | Optimal reproductive effort in fluctuating environments[END_REF][START_REF] Orzack | Population dynamics in variable environments. The demography and evolution of iteroparity[END_REF][START_REF] Gaillard | Temporal variation in survival of mammals: A case of environmental canalization?[END_REF]. Likewise, producing each year the same limited number of offspring (Olofsson, Ripa & Jonsén 2009) and adjusting reproductive effort to a low level relative to available resources to avoid jeopardizing survival [START_REF] Richard | Life in the slow lane[END_REF][START_REF] Gaillard | Temporal variation in survival of mammals: A case of environmental canalization?[END_REF][START_REF] Hamel | Fitness costs of reproduction depend on life speed: empirical evidence from mammalian populations[END_REF], Nevoux et al. 2010[START_REF] Jones | Primates and the evolution of long, slow life histories[END_REF]) correspond to a risk-minimizing life history tactic.

However, besides varying the number of offspring produced over breeding attempts during their lifetime, mothers in long-lived iteroparous organisms may change the phenotype of these offspring by allocating differentially among offspring within a given reproductive attempt (see [START_REF] Kühl | The "big spenders" of the steppe: sex-specific maternal allocation and twinning in the saiga antelope[END_REF] for evidence of differential maternal allocation to male offspring according to litter composition in saiga antelope Saiga tatarica). Such a mechanism involving developmental plasticity among litter mates has been called coin-flipping by [START_REF] Kaplan | The evolution of developmental plasticity in reproductive characteristics: An application of the "Adaptive Coin-Flipping" principle[END_REF]. Few studies have reported a phenotypic plasticity in offspring traits (Table 1).

Of 208 studies citing the Kaplan & Cooper's study on 12 January 2012, only 24 tested developmental plasticity of offspring phenotypic traits or diversification of developmental time. Most of them dealt with cold-blooded organisms as originally targeted by [START_REF] Kaplan | The evolution of developmental plasticity in reproductive characteristics: An application of the "Adaptive Coin-Flipping" principle[END_REF]. Only two studies dealt with warm-blooded species (house wrens, Troglodytes aedon, and yellow-bellied marmots, Marmota flaviventris) and provided support for the coinflipping hypothesis. In these cases, evidence for developmental plasticity of offspring was reported among litters (Table 1), leaving open the question of the possible existence of developmental plasticity within a litter.

In polytocous mammals, variation among females in phenotypic traits, genotype, and habitat quality leads offspring produced by different mothers within a cohort to be more dissimilar than litter mates, generating so-called family effects (sensu [START_REF] Gaillard | Family effects on growth and survival of juvenile roe deer[END_REF], see Pettorelli & Durant 2007 for a case study on carnivores). The dependence of offspring traits to maternal condition (i.e., condition-dependent state sensu McNamara & Houston 1996) has been repeatedly reported in mammals (see Clutton-Brock 1991 for a review) and corresponds to an individual optimization of the trade-off between size and number of offspring (Smith & Fretwell 1974[START_REF] Lloyd | Selection of offspring size at independence and other Size-Versus-Number strategies[END_REF]. While a trade-off between number and size of offspring is expected (e.g. Smith andFretwell 1974, Stearns 1992; see [START_REF] Saether | Ecological correlates of individual variation in age at maturity in female moose (Alces alces) -The effects of environmental variability[END_REF] in mammals), it is rarely observed because of heterogeneity in individual quality [START_REF] Van Noordwijk | Acquisition and allocation of resources: their influence on variation in life history tactics[END_REF]. Thus, large females usually produce large litters of large offspring, whereas small females produce small litters of small offspring, leading to strong family effects. This is in apparent contradiction with the coin-flipping hypothesis involving a decoupling between female attributes and early development of offspring so that females should produce a mixture of large and small offspring. This discrepancy might explain why evidence for coin-flipping has not been yet investigated in large mammals for which a tight link between mother and offspring phenotypes is commonly reported [START_REF] Clutton-Brock | The evolution of parental care[END_REF].

In the present work we aim to fill the gap by using a long-term detailed study on a wild boar (Sus scrofa scrofa) population. Wild boar is an especially relevant model to test for coinflipping because females produce large litter sizes (up to 14, see [START_REF] Servanty | Litter size and fetal sex ratio adjustment in a highly polytocous species: the wild boar[END_REF] they mostly feed on forest mast, the abundance of which fluctuates among years [START_REF] Servanty | Litter size and fetal sex ratio adjustment in a highly polytocous species: the wild boar[END_REF].

Using the long-term monitoring of the heavily hunted wild boar population at Châteauvillain-Arc-en-Barrois, we first tested for individual optimization predicting that large females should produce large litters while small females should produce small litters. We thus assessed the relationship between fetus mass and female body mass as well as the relationship between litter size and female body mass to check for the expected dependence between these two variables and female phenotype [START_REF] Clutton-Brock | The evolution of parental care[END_REF]. As mass at birth markedly influences future survival (Stearns 1992[START_REF] Roff | Life history evolution[END_REF], especially in large mammals [START_REF] Gaillard | Body mass and individual fitness in female ungulates: bigger is not always better[END_REF], individual optimization should also lead to marked family effects to allow large females to recruit more than small ones. To test explicitly the coin-flipping hypothesis, we investigated developmental plasticity by both evaluating intra-and inter-litter variance of offspring mass.

Under the coin-flipping hypothesis, females should produce a mixture of heavy and light offspring within a litter.

Materials and methods

STUDY AREA AND DATA COLLECTION

We studied a wild boar population in northeastern France in the 11,000 ha forest of Châteauvillain-Arc-en-Barrois. The territory is administratively divided into a core area that covers 8,500 ha of national forest and a 2,500 ha surrounding area of private or communal forest. These forests are mainly composed of oak (Quercus petraea), beechnut (Fagus sylvatica) and hornbeam (Carpinus betulus). The climate is intermediate between continental and oceanic types. Wild boars are hunted each year between October and February. Between 1995 and 2009, we recorded the dressed body mass (i.e., body mass without digestive tract, heart, lungs, liver, reproductive tract and blood) of each harvested female. Data on female reproductive status were also collected based on the examination of uteri for the presence of embryos or fetuses. Litter size was recorded and each fetus was weighed, measured (crownrump length, in millimeters), and sexed. This information was available for 319 females and 1,743 fetuses collected during 14 hunting seasons.

LINKING MASS OF FETUSES AND GESTATION STAGE

Offspring mass is expected to differ markedly among litters. In particular, not all litters were at the same gestation stage because females were shot at different dates and also because mating of wild boar occurs throughout most of the year in the study population, with a birth peak in mid-April [START_REF] Gamelon | High hunting pressure selects for earlier birth date: wild boar as a case study[END_REF]. We thus needed to standardize fetus mass by gestation stage. To assess the gestation stage of a given litter, the mean length of fetuses in the litter was first calculated. Then, we applied the model provided first by [START_REF] Henry | Fetal development in european wild hogs[END_REF]

LINKING LITTER SIZE AND FEMALE BODY MASS

Under the hypothesis of individual optimization, large females should produce large litters of large offspring, whereas small females should produce small litters of small offspring. We thus first assessed whether larger females produced larger litters than smaller females by linking litter size to female body mass. We thus fitted three models (on a log-scale): a simple linear regression model, a quadratic regression model, and a segmented regression model (Toms & Lesperance 2003). AIC was used for model selection (Burnham & Anderson 2002).

LINKING MASS OF FETUSES WITH FEMALE BODY MASS

We assessed whether large females produced larger offspring than small females by assessing possible effects of maternal mass on fetus mass. To do this, we used linear mixed models with normal error terms. We included individual fetus mass as the response variable and mother identity as a random effect. In addition, we accounted for differences in gestation stage among litters (by including a quadratic regression as fixed effects) and for other potentially confounding factors, namely hunting season, female body mass, litter size, and fetus sex. AIC was used for model selection (Burnham & Anderson 2002).

WITHIN-LITTER VARIABILITY IN FETUS MASS

To provide a measure of within-litter variation in mass, we calculated the coefficient of variation (CV) of fetus mass for each litter. To correct fetus mass by gestation stage, we used the quadratic relationship linking fetus mass and gestation stage (see the section "Linking mass of fetuses and gestation stage" for further details) and we standardized all fetuses at the same gestation stage of 110 days (110 days corresponds to the latest gestation stage observed in the dataset). To assess the effect of female body mass on the CV of fetus mass corrected for gestation stage, we fitted a linear regression between CV of fetus mass and female body mass.

Moreover, we explicitly tested whether the variation in fetus body mass increased with female body mass by including variance functions into the different models tested. We used the "varPower" variance function [START_REF] Pinheiro | Mixed-effects models in S and S-PLUS[END_REF] because of its flexibility. Models including variance functions only differ from models without variance function in that the within-group errors are allowed to be heteroscedastic. More precisely, the residual term of the regression linking fetus mass and female body mass followed a Gaussian distribution with mean zero and a variance that equals σ²*female body mass^(2*δ) where σ is the standard residual standard deviation and δ a parameter to be estimated. Including variance functions thus specifies that the variance in fetus mass changes with increasing female body mass [START_REF] Pinheiro | Mixed-effects models in S and S-PLUS[END_REF]; see [START_REF] Cleasby | Neglected biological patterns in the residuals a behavioural ecologist's guide to co-operating with heteroscedasticity[END_REF] for an application of variance functions). AIC was used for model selection (Burnham & Anderson 2002).

All these analyses were performed with R 2.12.2 (R Development Core Team 2011).

Results

LINKING MASS OF FETUSES AND GESTATION STAGE

As expected, the mass of fetuses increased with the gestation stage, on a quadratic way (gestation stage: slope = -17.175, SE = 0.371; p-value << 0.01; gestation stage²: slope = 0.209, SE = 0.003; p-value << 0.01; R² = 0.974; Appendix S1).

LINKING LITTER SIZE AND FEMALE BODY MASS

The segmented regression linking litter size with maternal mass provided the best fit to data (AIC = 174.1; intercept = -1.29 (0.31); slope= 0.76 (SE: 0.08) before the threshold; R²= 0.219) when compared to the linear (AIC = 178.2; intercept= -0.67 (SE: 0.26); slope= 0.59 (SE: 0.06); R²= 0.204) and quadratic (AIC = 176.3; intercept= -6.23 (SE: 2.89); log(Female Body Mass)= 3.53 (SE: 1.50); log(Female Body Mass)²= -0.38 (SE: 0.19); R²= 0.214) models.

The higher the female body mass is, the larger is the litter size until a threshold mass (Fig. 1).

Above this threshold mass, litter size did not increase with body mass. This threshold corresponded to a female mass of 58.3 kg, at which litter size was about 6.2 fetuses.

Nevertheless, the AIC of the three tested models were very close and the differences among models did not seem to be biological significant for most of the observed range in female body mass. There was indeed a quite high variation in litter size both above and below the threshold value. Moreover, there was a positive relationship between litter size and body mass, but this relationship became weaker (quadratic model) or stopped to become constant (piecewise model) as female body mass increases. The relationship between litter size and female body mass thus appears positive but highly variable, and there is a limit on how many offspring females can produce on average.

LINKING MASS OF FETUSES WITH FEMALE BODY MASS

The baseline model of variation in fetus mass only included the quadratic effects of gestation stage and the random effect of mother identity. The best model retained (AIC=16962.28) included in addition the fixed effects of hunting season, mother body mass (0.295 (SE: 0.117)) and fetus sex )) (Table 2A; see Appendix S2 for parameter estimates). Fetus mass thus depended on maternal mass. The heavier the females are, the heavier the fetuses are (Fig. 2). Nevertheless, from a biological viewpoint, this relationship between fetus mass and female body mass was weak as shown by the small effect size (maternal mass effect=0.2952 (SE: 0.1172)). Moreover, we found no effect of litter size on fetus mass.

WITHIN-LITTER VARIABILITY IN FETUS MASS

The heavier the female body mass is, the higher is the CV of fetus mass (intercept: -3.276e-03; slope = 3.545e-04; SE = 8.478e-05; p-value << 0.01; Fig. 3), meaning that the difference in terms of fetus mass within a litter produced by a heavy female was higher than the difference within a litter produced by a light female.

By including variance function into the different mixed models tested (Table 2B), we found that the best model retained among all the models presented in Table 2 included effects of hunting season, of mother body mass and of fetus mass as fixed effects, of mother identity as random effect and included the variance function (AIC=16842.07; see Appendix S2 for parameter estimates). We therefore found a marked increase in the log-likelihood associated with the inclusion of the variance function. Consequently, in the best model retained the variance in fetus mass increases with female body mass. More precisely, δ was estimated to

Discussion

We identified a continuum of reproductive tactics in wild boar females depending on their body mass. At one end, light females adjusted the size of their litters to their body mass. This was consistent with the individual optimization process involving a strong positive link between litter size and mother's phenotypic attributes usually reported in mammals (see [START_REF] Clutton-Brock | The evolution of parental care[END_REF][START_REF] Gaillard | Body mass and individual fitness in female ungulates: bigger is not always better[END_REF] body mass of female wild boar had a little influence on offspring mass. Fetus mass was mainly influenced by gestation stage, sex, and year. The influence of gestation stage is trivial and simply corresponds to fetal growth during gestation. Males were heavier than females, as expected for a polygynous and dimorphic species like wild boar [START_REF] Glucksmann | Sexual dimorphism in mammals[END_REF]). The marked among-year variation in fetus mass was also expected from the highly variable and unpredictable food resources wild boars face with. Finally, we did not detect any effect of litter size on fetus mass. This absence of any evidence for a trade-off between fetus mass and litter size is especially noteworthy. This indicates that these females adjusted their reproductive effort mainly through variation in litter size, and suggests that it pays more for females acquiring an energy surplus to produce more offspring than to produce heavier offspring. At this end of the continuum, we showed that light females produced fetuses that have very similar mass. Indeed, the CV of fetus mass was lower in litters produced by light females than in litters produced by heavy females, indicating little differences in fetus mass within litters produced by light females.

At the other end of the continuum, heavy females produced a quite large variation in litter size (from 3 to 11). Moreover, we showed that after a threshold body mass, additional body [START_REF] Jordan | The lifetime costs of increased male reproductive effort: courtship, copulation and the Coolidge effect[END_REF]. In other words, when diminishing returns occur, a doubling of reproduction provides less than a doubling of relative success [START_REF] Frank | Evolution in a variable environment[END_REF]). In our case, the litter size per-unit female body mass decreases as body mass increases, providing evidence for a marginal diminishing return. Therefore, heavy wild boar females did not show any evidence for an individual optimization of their reproductive effort. Such a total independence between female phenotypic attributes and size or number of offspring produced despite a twofold variation in litter size has not been yet reported in any mammalian species to our knowledge. Under the Lack model of optimal litter size [START_REF] Lack | The significance of Litter-Size[END_REF], selection should act on parents to maximize the number of offspring recruited, leading a trade-off to occur between number and size of offspring produced (Smith & Fretwell 1974[START_REF] Lloyd | Selection of offspring size at independence and other Size-Versus-Number strategies[END_REF][START_REF] Winkler | Offspring size and number: A life history model linking effort per offspring and total effort[END_REF]. Producing a lot of unviable offspring is obviously not a sustainable reproductive tactic, and producing a lot of large fetuses was not possible. The reproductive tactic displayed by most females of large mammals in response to these constraints involves optimizing this number-size trade-off according to their condition (individual optimization, [START_REF] Pettifor | Individual optimization of clutch size in great tits[END_REF], McNamara & Houston 1996). In addition, we showed that CV of fetus mass was higher in litters produced by heavy females than in litters produced by light females, indicating marked differences in fetus mass within litters produced by heavy females. Such a pattern of variation in within-litter fetus mass variation according to female body mass provides support for coin-flipping in litters produced by heavy females. Consequently, the high phenotypic diversity of offspring observed in litters produced by heavy females could thus result from multiple paternities.

Wild boar females, depending on their body mass, have thus different reproductive tactics, maybe facilitated by the fact that wild boar piglets are not dependent on their size to survive [START_REF] Baubet | Growth and survival in piglets[END_REF] contrary to other large mammalian species of herbivores [START_REF] Gaillard | Body mass and individual fitness in female ungulates: bigger is not always better[END_REF]. In absence of survival costs in small-sized piglets, wild boar females can produce a large range of offspring phenotypes. These females diversified the phenotype of their offspring, likely to minimize variance in reproductive success among years in the highly variable and unpredictable environment they faced with. Such a developmental plasticity might indeed allow females to recruit successfully in both mast years and years without any mast. Theoretical approaches have also shown that life cycle delays could increase fitness when environments are sufficiently variable (Tuljapurkar 1990;[START_REF] Tuljapurkar | Escape in time: stay young or age gracefully?[END_REF].

Previous studies of coin-flipping (Table 1) have shown that a large range of organisms adjust the number, the birth timing, and the phenotype of their offspring to maximize the number of recruits in fluctuating environments. However, these empirical studies focusing on development rate, asynchrony of hatchling, or dispersal capacities of offspring most often dealt with cold-blooded invertebrates, fishes, amphibians and reptiles. Kaplan Wild boars are hunted in most European forests and have become short-lived animals despite of their large body size. The generation time in heavily hunted wild boar populations is around 2 years, which is closer to the turn-over of tit populations than to that of a 60 kg mammal [START_REF] Servanty | Influence of harvesting pressure on demographic tactics: implications for wildlife Tuljapurkar, S. (1990) Delayed reproduction and fitness in variable environments[END_REF]. Such unusual demographic patterns have led wild boar females to have only one or two breeding attempts during their lifetime, starting to breed at one year of age [START_REF] Gamelon | High hunting pressure selects for earlier birth date: wild boar as a case study[END_REF]) at a low threshold body mass (between 20 and 25 kg, Servanty et al. 2009). Consequently, wild boar females could exhibit different reproductive tactics during their life according to their body mass. An investigation of coin-flipping in an un-hunted wild boar population in which individuals start to breed at a higher threshold body mass would be required to test whether all heavy females display a coin-flipping tactic. The vertical solid lines correspond to the threshold body mass estimated from the segmented regression and its associated confidence interval. Year 2008 -7.141294 13.387191 -17.448597 11.290648 -7.348290 10.329227 -18

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  to link gestation stage to mean fetus length across litters (gestation stage (in days) = 23.43+0.32* mean length (in mm)). The strength of this relationship was very high (R 2 = 0.86, N = 20, . The gestation stage was thus estimated from Henry (1968)'s model for each litter. We then regressed individual fetus mass of the entire dataset on the gestation stage and used the best model to standardize fetus mass at a given gestation stage. Because the relationship was quadratic (see Results), we corrected in all the following analyses the individual fetus mass by gestation stage and gestation stage² by including them as fixed effects.

  (with a 95% confidence interval of 0.812-1.156) meaning that the variance increases with the square of female body mass.

  translated into additional offspring. This stabilization corresponds to 6 fetuses on average. This could involve diminishing returns with increasing already large litters. Such diminishing returns have been reported in several studies (e.g., Jordan & Brooks 2010 on guppies Poecilia reticulate). Such a diminishing return can arise either because the marginal benefits of continued effort decrease or because the marginal costs of further reproductive effort increase

  identify a continuum of reproductive tactics in wild boar females. At one end, light females display an individual optimization tactic by producing a litter size depending on their body mass with fetus of similar mass. At the opposite end of the continuum, heavy females show a coin-flipping tactic by producing offspring with a highly diversified phenotype. The mating system in this wild boar population could provide a pathway for such a pattern related to coin-flipping. Indeed, recent works in the studied population have shown that the number of fathers within a litter increased with litter size(Devillard et al. unpublished data). Nevertheless, large litters are generally produced by heavy females (Fig.1).

  themselves, in their original paper, focused on cold-blooded organisms certainly because developmental plasticity of offspring in warm-blooded species is expected to be constrained by thermoregulation.

  .M. & Houston, A.I. (1996) State-dependent life histories. Nature, 380, 215-221. Meffe, G. K. (1987) Embryo size variation in mosquitofish: Optimality vs plasticity in propagule size. Copeia, 3, 762-768. Menu, F. & Debouzie, D. (1993) Coin-flipping plasticity and prolonged diapause in insects: example of the chestnut weevil Curculio elephas (Coleoptera: curculionidae). Oecologia, 93, 367-373. Menu, F., Ginoux, M., Rajon, E., Lazzari, C.R. & Rabinovich, J.E. (2010) Adaptive developmental delay in chagas disease vectors: An evolutionary ecology approach. PLoS, neglected tropical diseases, 4, e691. Moore, G.H., Littlejohn, R.P. & Cowie, G.M. (1988) Factors affecting live weight gain in red deer calves from birth to weaning. New Zealand journal of agricultural research, 31, 279-283. Murphy, G.I. (1968) Pattern in life history and the environment. The American Naturalist, 102, 391-403. Nevoux, M., Forcada, J., Barbraud, C., Croxall, J. & Weimerskirch, H. (2010) Bet-hedging response to environmental variability, an intraspecific comparison. Ecology, 91, 2416-2427. Olofsson, H., Ripa, J. & Jonzén, N. (2009) Bet-hedging as an evolutionary game: the trade-off Journal of Applied Ecology, 48, 835-843. Slatkin, M. (1974) Hedging one's evolutionary bets. Nature, 250, 704-705. Smith, C. C. & Fretwell, S.D. (1974) The optimal balance between size and number of offspring. The American Naturalist, 108, 499-506. Stearns, S.C. (1992) The evolution of life histories, vol. 248. Oxford University Press Oxford. Tanaka, K. (1995) Variation in offspring size within a population of the web-building spider Agelena limbata. Researches on Population Ecology, 37, 197-202. Thumm, K., & Mahony, M. (2002) Hatching dynamics and bet-hedging in a temperate frog, Pseudophryne australis (Anura: myobatrachidae). Amphibia-Reptilia, 23, 433-444. Thumm, K., & Mahony, M. (2005) Is variable egg size the proximate cause of diversified bet-hedging in the hatching dynamics of the red-crowned toadlet (Pseudophryne australis)(anura: Myobatrachidae)? Journal Information, 61, 9-19. Thumm, K., & Mahony, M. (2006). The effect of water level reduction on larval duration in the red-crowned toadlet Pseudophryne australis (Anura: myobatrachidae): Bet-hedging or predictive plasticity? Amphibia-Reptilia, 27, 11-18. Toms, J. & Lesperance, M. (2003) Piecewise regression: a tool for identifying ecological thresholds. Ecology, 84, 2034-2041.

  List of the 24 papers (out of 208 quoting[START_REF] Kaplan | The evolution of developmental plasticity in reproductive characteristics: An application of the "Adaptive Coin-Flipping" principle[END_REF]'s paper on coinflipping on 12 January 2012) including tests of phenotypic polymorphism among offspring produced by a given individual. The species considered in the study, the taxonomic order, the offspring trait measured, the test outcome (coin-flipping (yes) or no (no)), and the reference of the study are provided. The table is divided into two parts. Part A brings together studies showing a developmental plasticity of offspring while part B brings together studies showing diversification of developmental time. Warm-blooded organisms occur in bold.

Figure legends Figure 1 .

 legends1 Figure legends

Figure 2 .

 2 Figure 2. Relationship between standardized fetus mass (i.e., corrected for gestation stage)

Figure 3 .

 3 Figure 3. Relationship between the CV of fetus mass and female body mass from females

  at each reproductive attempt and face highly variable and unpredictable environmental conditions as

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  for reviews). However, while previous studies of large mammals have reported that mothers in better than average condition produce heavier offspring (e.g., Russell et al. 1981 and Holst, Killeen & Cullis 1986 for sheep Ovis aries; Blaxter & Hamilton 1980, Moore, Littlejohn & Cowie 1988 for red deer Cervus elaphus),

Table 2 .

 2 Model selection of linear mixed models fitted with individual fetus mass (mass) as a response variable and mother identity (mother) as a random factor. The fixed effects correspond to gestation stage (gestation) and gestation stage² (gestation²), hunting season (year), fetus sex (sex), mother body mass (mother body mass) and litter size (litter size). Displayed are the AIC of each model and the difference in AIC between each candidate model and the best model (∆AIC) for (A) all possible models presented in the column Models and for (B) the models presented in the column Models with a variance function specifying that fetus mass was allowed to differ in relation to female body mass. The selected models are in bold. Data come from wild boar females collected in the population of Châteauvillain-Arc-en-Barrois, France.

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Journal of Animal Ecology

Acknowledgments

We are grateful to all those who helped capturing and marking wild boars, as well as those who helped collecting harvested wild boars, particularly P. Van den Bulck and G. Corbeau. We are grateful to the Office National des Forêts and to F. Jehlé, who allowed us to work on the study area.We warmly thank Tim Coulson, Marco Festa-Bianchet, Mark Hewison, Barry Sinervo and Shripad Tuljapurkar for their helpful comments on previous drafts. We also thank two anonymous referees and Atle Mysterud for constructive comments on previous drafts. 14.395004 -15.2758 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 10.755132 -28.282855 10.653286 10.032485 -11.217519 11.132955 -4.234911 10.756089 -28.205192 10.680299 9.962937 -10.888894 11.062900 -4.099329 10.731061 -27.942114 10.629121 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 15.569515 -26.756219 10.478344 0.351154 0.134593 -0.761081 15.557201 -26.979810 10.467356 0.306138 0.122347 NA 15.607521 -26.566817 10.501591 0.291162 0.122808 NA 15.757725 -24.087746 10.573349 NA NA 0.215009 15.734505 -23.912606 10.533042 NA NA NA 15.721065 -24.408989 10.548713 NA NA 0.261294 15.698815 -24.196305 10.509310 NA NA NA NA NA NA 0.282717 0.133937 -1.200203 NA NA NA 0.193927 0.122168 NA NA NA NA NA 0.134642 -1.203652 NA NA NA 0.211577 0.121554 NA NA NA NA NA NA -0.409210 NA NA NA NA NA -0.35464 NA NA NA NA NA NA NA NA NA NA NA NA 15.447044 -23.3331 10.499089 0.3273 0.138936 -0.8522 15.380652 -23.5533 10.460556 0.3385 0.138557 -0.8335 15.372358 -23.8115 10.451039 0.2847 0.124049 NA 15.440075 -23.5974 10.490455 0.2725 0.124459 NA 15.556002 -21.1073 10.533739 NA NA 0.1489 15.530104 -20.9634 10.485826 NA NA NA 15.496929 -21.2527 10.500213 NA NA 0.2027 15.471946 -21.0580 10.452921 NA NA NA NA NA NA 0.2856 0.957919 -1.2620 NA NA NA 0.1892 0.123598 NA NA NA NA 0.2716 0.138223 1422 -1.2772 NA NA NA 0.2039 0.123032 NA NA NA NA NA NA -0.4280 NA NA NA NA NA -0.3685 NA NA NA NA NA NA NA NA NA NA NA NA

Supporting Information

Appendix S1

Relationship between fetus mass and gestation stage in the wild boar population of Châteauvillain-Arc-en-Barrois, France (gestation stage: slope = -17.175, SE = 0.371; p-value << 0.01; gestation stage²: slope = 0.209, SE = 0.003; p-value << 0.01; R² = 0.974).