Accepted Article

Received Date : 20-Sep-2013 Accepted Date : 05-Jun-2014 Article type

: Standard Paper

Editor

: Christiaan Both

Section

: Evolutionary Ecology

Fitness prospects: effects of age, sex and recruitment age on reproductive value in a long-lived seabird

He Zhang1, Maren Rebke2, Peter H. Becker1 and Sandra Bouwhuis1

1

Institute of Avian Research ‘Vogelwarte Helgoland’, An der Vogelwarte 21, D-26386, Wilhelmshaven, Germany, 2

Avitec Research GbR, Sachsenring 11, D-27711, Osterholz-Scharmbeck, Germany.

Corresponding author: [email protected]

Abstract (1) Reproductive value is an integrated measure of survival and reproduction fundamental to understanding life-history evolution and population dynamics, but little is known about intraspecific variation in reproductive value and factors explaining such variation, if any. (2) By applying generalized additive mixed models to longitudinal individual-based data of the common tern Sterna hirundo we estimated age-specific annual survival probability, breeding

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probability and reproductive performance, based on which we calculated age-specific reproductive values. We investigated effects of sex and recruitment age on each trait. (3) We found age effects on all traits, with survival and breeding probability declining with age, while reproductive performance first improved with age before levelling off. We only found a very small, marginally significant, sex-effect on survival probability, but evidence for decreasing age-specific breeding probability and reproductive performance with recruitment age. (4) As a result, males had slightly lower age-specific reproductive values than females, while birds of both sexes that recruited at the earliest ages of 2 and 3 years (i.e. 54% of the tern population) had somewhat higher fitness prospects than birds recruiting at later ages. While the recruitment age effects on breeding probability and reproductive performance were statistically significant, these effects were not large enough to translate to significant effects on reproductive value. (5) Age-specific reproductive values provided evidence for senescence, which came with fitness costs in a range of 17-21% for the sex-recruitment age groups. (6) Our study suggests that intra-specific variation in reproductive value may exist, but that, in the common tern, the differences are small.

Keywords: age at first reproduction, sexual dimorphism, life-history evolution

Introduction Knowledge of a species’ age-specific pattern of survival and reproduction is fundamental to understanding its life-history evolution and population dynamics (Stearns 1992). Reproductive value, an integrative fitness measure developed by Fisher (1930), is extremely useful in this respect, as it combines estimates of age-specific survival and reproductive performance to predict the number of

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offspring an individual can expect to obtain during the remainder of its life, and hence assesses the relative contribution of individuals of different ages to population growth (Stearns 1992; Sæther et al. 2013). Age-specific reproductive values have been investigated in few species, mainly birds (Newton & Rothery 1997; Møller & De Lope 1999; Bonduriansky & Brassil 2002; Keller, Reid & Arcese 2008; Brown & Roth 2009; Bouwhuis et al. 2012), but, in general, seem to show an inverse U-shaped pattern and thus provide evidence for life-histories that include improvement in early life, followed by a late-life performance decline (i.e. senescence).

Besides age-specific reproductive values being scarcely reported, virtually nothing is known about intra-specific variation in these values and factors explaining such potential variation, although many studies have examined intra-specific variation in age-specific survival and reproductive performance separately (Reed et al. 2008; Kawasaki et al. 2008; Nussey et al. 2009; Zajitschek et al. 2009; Bouwhuis et al. 2010a; b). As the two exceptions we are aware of, age-specific reproductive values were reported for males and females separately for two short-lived songbirds, the song sparrow Melospiza melodia and the wood thrush Hylocichla mustelina. In the song sparrow, reproductive values seemed somewhat higher in females than males, while declining markedly in old age in both sexes (Keller et al. 2008). Such a sex difference would fit with predictions of males adopting a ‘live fast, die young’ life history strategy as a result of sexual selection (e.g. Bonduriansky et al. 2008). In the wood thrush, however, reproductive values of both sexes were similar and also declined in old age (Brown & Roth 2009). More studies are therefore needed to assess sex differences in reproductive values, as well as studies to investigate other, so far neglected, factors that might cause individuals to have different age-specific reproductive values.

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Another candidate trait related to performance measures in many species is recruitment age, defined as the age at first-time initiation of reproduction, variation in which is potentially underpinned by genes (e.g. Charmantier et al. 2006), maternal effects (e.g. Pettay et al. 2005), nutrition or environmental conditions (e.g. Langvatn et al. 1996). Studies of recruitment age have found early recruitment to be associated with beneficial trait values, such as early calving date and increased birth weight in red deer Cervus elaphus (Nussey et al. 2006), early arrival date in common terns (Becker et al. 2008), increased lifetime reproductive success in mute swans Cygnus olor (Charmantier et al. 2006), European badgers Meles meles (Dugdale et al. 2011), blue-footed boobies Sula nebouxii (Kim et al. 2011) and humans (Bolund et al. 2013), and reduced rates of reproductive senescence in blue tits Cyanistes caeruleus ogliastrae (Auld & Charmantier 2011). On the other hand, early recruitment has also been found to be associated with unfavourable trait values, such as reduced survival in rhesus macaques Macaca mulatta (Blomquist 2009), increased rates of reproductive senescence in blue-footed boobies (Kim et al. 2011) and a later onset of reproduction late in life in blue tits (Auld & Charmantier 2011). Finally, no effects of recruitment age were found on age-dependent survival or traits linked with breeding performance in black-browed or wandering albatrosses Thalassarche melanophrys and Diomedea exulans (Froy et al. 2013; Pardo et al. 2013). One reason why different relations between recruitment age and fitness-related traits may have been observed is that, within species, traits may be traded off against each other. Alternatively, between species, different traits may be canalized or be susceptible to change with age or environmental variation (Hamel et al. 2010; Arnaud et al. 2013). Therefore, only a composite fitness measure may be able to provide insight into the generality of recruitment age effects when the underlying mechanisms differ. To initiate establishing such general patterns, as well as to measure the total impact of recruitment age on fitness, we suggest studying whether the integrated fitness measure of reproductive value varies with recruitment age.

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In this paper, we focus on the common tern, a long-lived colonial seabird, and use data collected as part of a longitudinal individual-based population study of a breeding colony on the German North Sea coast. Previous studies of aspects of recruitment age and age-specific performance in the common tern have found i) a sex difference in the process and timing of recruitment, with female terns recruiting earlier than males (Ludwigs & Becker 2002; Nisbet & Cam 2002; Ezard, Becker & Coulson 2006); ii) a complex interplay of recruitment age and breeding experience which influenced the degree of early-life improvement in reproductive performance (Limmer & Becker 2010); and iii) reproductive senescence which occurred after a long period of improvement in performance and seemed to be more pronounced in females than males (Rebke et al. 2010; Rebke 2011). We build on these results by estimating age-specific, sex-specific and recruitment age-specific survival probabilities, breeding probabilities, reproductive performance and reproductive values.

Material and Methods (a) Study population Longitudinal individual-based data were collected from a common tern colony located at the Banter See in Wilhelmshaven, on the German North Sea coast (53°36'N, 08°06'E). The study has run since 1992, when 101 adults were marked with individually numbered subcutaneously injected transponders (TROVAN ID 100; TROVAN, Köln, Germany) and since when every fledgling has similarly been marked with such a transponder (Becker, Wendeln & González-Solís 2001; Becker 2010). The colony site consists of six rectangular concrete islands, each of which measures 10.7*4.6 m and is surrounded by a 60 cm wall. The walls support 44 platforms for terns to land and rest on. Each platform is equipped with an antenna which reads transponder codes at a distance of ≤ 11 cm every

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5 - 10 seconds and therefore automatically records the presence of transponder-marked individuals. During incubation, which is shared between partners, additional antennae are placed at each nest for 1 – 2 days to identify breeding individuals (Becker & Wendeln 1997; Becker et al. 2001). Combined with regular checks of each nest to record reproductive parameters and to mark offspring with rings and transponders, these methods enable the systematic and remote documentation of individual life cycles with an extremely high detection probability (e.g. 100% detection for breeding individuals, Szostek & Becker 2012). Since 1992, the number of breeding pairs has ranged between 90 and 530 (Szostek & Becker 2012).

After the breeding season, common terns migrate to western Africa. Local recruits return to the breeding colony from an age of 2 years to prospect or to initiate reproduction (Ludwigs & Becker 2002; Becker et al. 2008). We define recruitment age (RA) as the age of first breeding at the Banter See (i.e. it is the local recruitment age), which could reliably be established for birds hatched after 1989. Following previous studies from our population, we define four RA groups: 2, 3, 4 and 5+ years (cf. Ludwigs & Becker 2002; Limmer & Becker 2010), of which three-year recruits form half of the breeding population (table 1). The sex of transponder-marked birds has been determined by standard molecular methods since 1998 (Becker & Wink 2003) and by behavioural observations before that.

(b) Data and statistical analyses Our data, based on locally hatched and transponder-marked individuals, contain 423 males and 359 females, of known age and RA, with 2305 and 2068 bird-years from first reproduction, respectively, and cover the breeding seasons 1993 – 2011. ‘Annual survival’ of each individual was determined by checking whether it was registered by the antenna system in any of the breeding seasons 1993 -

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2013. We thus assume death, rather than directly observe it, but we assess the reliability of this assumption to be high, as 97% of breeders do not skip observation for two or more consecutive years since first reproduction (Zhang et al., under review). Note, however, that our measure of survival, like that of RA, is local and may include permanent emigration from the study area, although our high estimates of local survival (see Results) suggest that permanent emigration must be rare. ‘Breeding probability’ captured whether birds were observed breeding at the Banter See or not. Non-breeding status included observed skipped breeding (registration of non-breeding individuals in the colony), as well as missing observations (458 bird-years in total), such that breeding probability, as RA and survival probability, is a local measure. For breeding birds, our measure of local reproductive success was the annual number of chicks fledged per pair, including those from replacement (10.0%) and second (0.9%) clutches.

Generalized additive mixed models (GAMMs, Wood 2006) were employed to investigate effects of age, sex and RA on annual survival probability, breeding probability and reproductive success. To avoid pseudo-replication, reproductive success data were obtained by randomly including only one of the partners of each breeding attempt if both individuals were marked with transponders (979 pairs). For annual survival probability and reproductive success analyses, data started at the onset of breeding in each RA group, while for annual breeding probability they started from the year after the onset of breeding because data before that were fixed for a given RA (i.e. birds had to survive, but not reproduce, until RA). Note that this means that we do not consider prereproductive mortality in our analyses and focus on the local fitness prospects of birds that managed to survive to reproduction only. As non-breeders are not necessarily site-faithful, we currently, however, do not have the means to accurately estimate age-specific pre-recruitment survival probabilities.

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The response variables ‘annual survival probability’ and ‘annual breeding probability’ were fitted using a binomial distribution with a ‘logit’ link function, while ‘annual reproductive success’, with values ranging from 0-3 with a mean and variance of 0.71 and 0.65, respectively, was assumed to follow a Poisson distribution with a ‘log’ link function. To account for the non-independence of repeated observations and environmental variation, individual identity and calendar year were used as random effects, each of which was assumed to follow a normal distribution with a mean of zero. Note that we were not interested in the year effect itself, but rather aimed to account for variation caused by the different conditions in the different years, and hence used year as a random rather than as a fixed effect, although we also ran additional models in which year was treated as a fixed effect (see below). Models with fixed effects of age in the form of a smooth function, sex as a factor with males as the reference level, RA as a factor with RA3 as the reference level and their interactions were fitted and compared using Akaike’s Information Criterion (AIC, Burnham & Anderson 2004).

We performed five additional analyses. We i) investigated the effects of age and RA on reproductive success in males and females separately; and ii) reran the model with the lowest AIC value for annual reproductive success including relative partner age (i.e. the difference between the age of the focal individual and that of its partner) as a fixed effect with a smooth function. These additional analyses were run because common terns are known to be age-assortatively mated (Ludwig & Becker 2008, fig. A1), which will reduce the scope for the evolution and detection of sexual dimorphism in rates of ageing. We would, however, like to note that while age-assortative mating is statistically significant (Pearson’s correlation coefficient r = 0.684, p < 0.001, fig. A1), it is incomplete and its own age-dependence (Ludwig & Becker 2008) may allow for differences in reproductive senescence rates between the sexes (Rebke et al 2010). Moreover, while sex and

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recruitment age are static properties of an individual, it can be argued that acquisition of a mate of a certain age is a potentially dynamic property of the focal individual, investigation of which is of interest if we are to understand the proximate mechanisms underlying an individual’s age-specific reproductive value, but does not need to be taken into account to establish the general pattern.

We iii) reran all models with year as a fixed effect with a smooth function instead of as a random effect; and iv) reran the model for annual reproductive success with data excluding the cohorts of birds hatched between 1999 and 2006 (and hence potential breeders from year 2002 onwards). These additional analyses were run to ascertain that results from models using the full dataset were not driven by directional change in environmental conditions over time during the years 1992-2001, when the colony experienced an increase in breeding pairs and success, or the more recent deterioration of environmental circumstances between 2002-2009 (Szostek & Becker 2012). We would, however, also like to note that breeding success recovered from 2010 onwards, such that young and old birds in our dataset have all experienced a variety of environmental conditions.

Finally, we v) reran the model for annual reproductive success including a binary variable ‘last observation’. An effect of last observation would indicate terminal effects to occur, either negative through terminal illness (Coulson & Fairweather 2001; Rattiste 2004), or positive through terminal investment (Clutton-Brock 1984; Bonneaud et al. 2004).

Model parameters were estimated by Laplace approximation. R software (version 3.0.1) was used to apply the GAMMs with the function ‘gamm4’ in the package ‘gamm4’.

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(c) Reproductive value Reproductive value, as an integrated fitness measure, estimates the number of offspring that an individual in a particular age class can expect to obtain over the remainder of its life under the prevailing conditions, adjusted only by population growth rate (Stearns 1992). The formula we used , where the

to obtain age-specific reproductive values was survivorship

was the probability of surviving from birth to age x and

was the probability of surviving from age x to age x+1;

was the cumulative survival probability

from birth to age class x given that one had survived to age class a, offspring per pair at age x,

was the breeding probability at age x,

was the expected number of was the maximum age (i.e. 25

years) and r was the instantaneous rate of population growth, calculated by r =

(Stearns

1992), which was 0.08 between 1992 and 2011. For each sex-RA combination, we obtained predicted age-specific values of survival probability, breeding probability and reproductive success based on the best performing models for an age range of 2-25 years in order to calculate the corresponding age-specific reproductive values. We chose this age range because the maximum observed age in our population was 24 years in 2013.

The fitness cost of senescence, in terms of the loss of RV due to senescence, was defined as (RV2ns-RV2) / RV2ns, where RV2 denotes the observed reproductive value at age 2 and RV2ns represents the hypothetical reproductive value at age 2 if senescence were not to occur (Bonduriansky & Brassil 2002; Bouwhuis et al. 2012). We evaluated the cost of senescence due to each fitness component underlying RV by replacing RV2ns by RV2nss (RV2 if no survival senescence), RV2nbs (RV2 if no senescence in breeding probability) and RV2nrs (RV2 if no senescence in reproductive success), respectively. Because the absence of survival senescence would cause

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individuals to reach ages over 25, we extended the calculation of both the actual reproductive values and the hypothetical reproductive values for each combination of sex and RA to a hypothetical maximum age of 39, when even without survival senescence the probability of being alive would be below 0.06 (Bouwhuis et al. 2012). Senescence effects were therefore excluded by keeping survival probability, breeding probability and/or reproductive success constant from the age of peak performance after first breeding to the hypothetical age of 39.

By randomly generating 10,000 coefficients within a normal distribution derived using the obtained coefficient and variance matrix from the model with the lowest AIC value (i.e. posterior simulation, Wood 2006), we obtained 10,000 simulations for age-specific survival probability, breeding probability and number of fledglings. Herewith, we obtained 10,000 sets of age-specific reproductive values for each combination of sex and RA to calculate standard errors for the agespecific reproductive values and the fitness costs of senescence.

Results (a) Effects of age, sex and recruitment age on fitness components We found age effects on all traits (table 2, fig. A2). Annual survival probability was negatively related to age and declined from 0.93 to 0.73 between age 2 and 25 (fig. 1A, B). Annual breeding probability also showed a linear decline with age from 0.99 to 0.69 (fig. 1C, D). Reproductive success strongly increased up to age 13, peaking above one fledgling per pair and levelling off afterwards (fig. 1E, F). There were no effects of RA on survival probability. The age-effect on breeding probability was, however, supplemented with RA effects. The oldest recruits (5+ years) had the lowest breeding probability throughout life, while the breeding probabilities of the other RA groups did not differ (table A1, fig. 1C, D). The age-effect on reproductive success was also supplemented with RA effects:

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birds that recruited at the age of 2 and 3 produced most fledglings, while birds that recruited at age 4 or later had significantly lower reproductive success (table A1, fig. 1E, F). Excluding the cohorts of birds hatched between 1999 and 2006, or using year as a fixed effect in the model, did not change these results (fig. A3, A4).

The sexes differed marginally significantly in survival probability, with males surviving slightly less well than females (table A1, fig. 1A, B, fig. A2). There was, however, no sex effect on breeding probability or reproductive success, nor on the RA- or age-dependence of survival probability, breeding probability and reproductive success (table 2). For reproductive success, these results were confirmed in sex-specific analyses (table A2), and the age effect remained significant when adding relative partner age to the model (table A3).

There was no terminal effect on reproductive success, nor evidence for age- or RA-specific terminal effects (Table A4).

(b) Reproductive value Age-specific reproductive values were slightly higher in females than in males (fig. 1G, H), although the standard errors of the estimates overlapped (fig. A5). Birds that recruited at the ages of 2 and 3 had the highest age-specific reproductive values, with peaks of 5.1 fledglings per pair in males, and 5.5 fledglings per pair in females, while the oldest recruits (RA5+) had the lowest fitness prospects (fig. 1G, H), but again the standard errors of these estimates overlapped (fig. A5). The onset of senescence in reproductive value occurred at age 8 for all birds except males that recruited at the age of 3, for which it occurred at age 9, and the proportion of individuals that entered the life stage of senescence ranged between 24 - 46% (table 1). The total fitness cost of senescence did not differ

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between sex-RA groups, ranged between 17 and 21%, and was almost entirely caused by costs of survival senescence, which ranged between 12 and 17% (table 1).

Discussion Using an exceptional longitudinal individual-based dataset on the common tern, we added to the scarce existing data on reproductive values in natural populations by showing that while age, sex and recruitment age affect underlying fitness traits, only the age effect translated to intra-specific variation in reproductive values. The age-specific reproductive values provided evidence for senescence, which came with fitness costs in a range of 17-21% for the investigated sex-recruitment age groups.

Age-specific reproductive values have been investigated in few species (Newton & Rothery 1997; Møller & De Lope 1999; Bonduriansky & Brassil 2002; Keller, Reid & Arcese 2008; Brown & Roth 2009; Bouwhuis et al. 2012), but, in general, seem to show an inverse U-shaped pattern, providing evidence for life-histories that include improvement in early life, followed by late-life senescence. The age-specific reproductive values we report here for the common tern fit this general pattern, and our analyses of the underlying fitness traits suggest that early-life improvement is entirely due to a long-term improvement in fledgling production, while senescence late in life occurs when fledgling production levels off such that it no longer compensates for the age-specific declines in survival and breeding probabilities that start with the onset of reproduction. Specifying the fitness cost of senescence due to each component of the reproductive value shows that survival senescence is especially important, since the total fitness cost resulted almost completely from the linear decline in survival probability with age, while age-specific changes in breeding probability and reproductive success had hardly any effect. This contradicts theories of trait canalization, which

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suggest that in long-lived species, such as the common tern, in which fitness depends largely on future reproduction and in which canalization is thus expected to act against environmental variability in reproduction (Gaillard & Yoccoz 2003), costs of reproduction are more likely to be found in reproduction than survival (Hamel et al. 2010). Such an opposed pattern was also found in flies (Bonduriansky & Brassil 2002) and great tits (Bouwhuis et al. 2012), such that while trait canalization underlies the evolution of costs of reproduction (Hamel et al. 2010), trait canalization does not seem to underlie the evolution of senescence.

Previous work on fitness costs of senescence found that the cost of senescence was larger in long-lived than short-lived mammals (Bouwhuis et al. 2012). Interestingly, costs of senescence were found to be independent of peak survival rate in birds, but the peak survival rate of birds included in the analysis ranged from 0.49 to 0.81 and information on long-lived birds was lacking (Bouwhuis et al. 2012). We here found the peak survival rate of the common tern to be 0.93, hence substantially higher than that of the previously investigated bird species. We also found that the total fitness cost of senescence ranged between 17% and 21%, with the overall weighted average being 18.6%, which exceeded the 3.5 – 13.5% range found for six bird species investigated by Bouwhuis et al. (2012). When adding our data point to the interspecific comparison, the relationship between peak survival rate and the fitness costs of senescence in mammals and birds remains significantly different (class * peak survival rate: 86.323 ± 17.430, Χ21 = 24.526, p < 0.001), but the slope of the relationship within birds increases and becomes significantly positive (old slope: 7.99924 ± 14.962, Χ21 = 0.281, p = 0.596; new slope: 23.388 ± 10.975, Χ21 = 4.541, p = 0.033). Adding more long-lived bird species and understanding the cause of the difference between birds and mammals therefore remains an interesting challenge.

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Looking at the annual average age-distribution of our population and the age at the onset of senescence for the sex-RA groups, we found that over 24%, and up to 46%, of the common terns entered the life stage of senescence, while this value was 7% and 20% in female collared flycatchers Ficedula albicollis and great tits, respectively (Brommer, Wilson & Gustafsson 2007; Bouwhuis et al. 2012). Causes and consequences of variation in the proportion of individuals undergoing senescence in natural populations are currently unknown, but would make another really interesting avenue for future investigation. We would therefore like to urge studies on senescence to report these values.

Sexual dimorphism in age-specific reproductive values has not been formally discussed, but sex differences have been reported for ageing patterns of underlying fitness traits in various species. Male flies Telostylinus angusticollis, for example, showed more rapid survival senescence than female flies (Kawasaki et al. 2008), while this pattern was reversed in crickets Teleogryllus commodus (Zajitschek et al. 2009). Similarly, male reproductive success declined more rapidly with age than female reproductive success in red deer (Nussey et al. 2009), while females showed faster reproductive senescence than males in the common guillemot Uria aalge (Reed et al. 2008). While, classically, males have been predicted to adopt a ‘live fast, die young’ life history strategy as a result of sexual selection and have therefore been predicted to age more rapidly, evidence for this clearly is far from conclusive (Bonduriansky et al. 2008) and more studies, including those using a more complete fitness measure, are required. In the common tern, we found a marginally significant difference between the sexes in annual survival probability, which led to slightly lower reproductive values in males compared to females. While, qualitatively, the found sex difference in age-specific reproductive values resembles findings in song sparrows (Keller et al. 2008) and fits with predictions of males adopting a ‘live fast, die young’ life history strategy as a result of sexual selection (e.g. Bonduriansky et al. 2008), it does not hold quantitatively. Since the 75 percentiles for male and

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female reproductive values in song sparrows also largely overlapped (fig. 3 in Keller et al. 2008), we can conclude that therefore there currently is no evidence for sexual dimorphism in reproductive values.

Besides not finding evidence for sexual dimorphism in reproductive values, we also found no interaction of sex with age or RA in any of the traits investigated, suggesting no sex difference in ageing patterns to exist either. This again resembles findings in song sparrows and wood thrushes (Keller et al. 2008; Brown & Roth 2009), although we would like to note that common terns are socially and genetically monogamous and mate age-assortatively (Ludwig & Becker 2008, fig. A1), such that the the scope for the evolution and detection of sexual dimorphism in rates of ageing may be limited.

While a trade-off between RA and survival or lifespan was shown in the rhesus macaque (Blomquist 2009) and mute swan (Charmantier et al. 2006), no RA effect was found on age-specific survival probability in the black-browed albatross (Pardo et al. 2013), the wandering albatross (Froy et al. 2013) or in our study of the common tern. Instead, we found that younger recruits had a higher probability to breed and achieved higher annual reproductive success than older recruits if they did. Our finding of the oldest recruits, i.e. the ones recruiting at or after 5 years of age (9% of all breeding birds), having a low breeding probability throughout life can reflect two processes. First, these birds can truly skip breeding more often, and therefore be of poor individual quality. Alternatively, however, these birds may show reduced site fidelity throughout their breeding career and occasionally breed elsewhere. Detailed future study of sighting records of these skipping breeders will be required to distinguish between these two alternatives, and we are currently planning such work. Our finding of annual reproductive success of older recruits being lower than

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that of younger recruits, however, also suggests that early recruitment is a sign of individual quality, in line with findings in humans (Bolund et al. 2013) and other mammals, such as the European badger (Dugdale et al. 2011). Nevertheless, while RA differences in reproductive success resulted in age-specific reproductive values being highest in two- and three-year old recruits and in age-specific reproductive values decreasing with further increasing RA, the standard errors of the estimates overlapped, such that the difference should be considered with caution. We would, however, like to note that in our analyses, we do not consider pre-reproductive mortality and focus on the fitness prospects of birds that managed to survive to reproduction only. And while post-recruitment survival probabilities do not vary with RA, but survival probability declines with age, prereproductive mortality is likely to penalize old recruits more than young recruits. Our small suggested fitness costs of late recruitment is therefore likely to underestimate the complete fitness costs of late recruitment, but we do not have the means to accurately estimate age- and recruitment age-specific pre-recruitment survival probabilities.

In summary, we found evidence for varying age-specificity of fitness components, which translated into age-specific reproductive values, which included early-life improvement driven by reproductive performance, and late-life senescence driven by survival probability. Despite evidence for intraspecific variation in our fitness traits, in relation to sex and recruitment age, this variation was not large enough to be statistically significant at the integrated reproductive value level. We expect this may often be the case, because total fitness and its variation are derived via a multiplicative process, but would like to stress that investigating effects of traits on complete fitness measures is required if we are to understand evolutionary implications of trait variation.

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Acknowledgements We thank numerous field workers for compiling the long-term dataset and are grateful to the anonymous associate editor, two anonymous referees, O. Vedder, A. Scheuerlein and F. Colchero for their contribution to improving this paper. The study was performed under the license of the Bezirksregierung Weser-Ems and town Wilhelmshaven and supported by the Deutsche Forschungsgemeinschaft (BE 916/3 to 9) and ‘project Promotion plus’ from the Lower Saxon Ministry of Science and Culture.

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Tables Table 1. Sample size (number of individuals, number of bird-years and proportion of individuals), average annual proportion of individuals experiencing senescence in reproductive value (Sen), reproductive value (RV) at age 2 based on an age range of 2 to 25 (RV2), hypothetical RV at age 2 based on an age range of 2 to 39 (hRV2), hypothetical RV at age 2 when excluding senescence in survival probability (hRV2.nss), breeding probability (hRV2.nbs), reproductive success (hRV2.nrs) or all (hRV2.ns) and their associated fitness costs (in percentages) for each sex-recruitment age combination (M for males, F for females and recruitment ages 2, 3, 4 and 5+).

M2

N (birdyears, %) 6 (50, 0.8)

40.1

3.57 ±0.94

3.58 ±0.98

4.32 ±1.17

3.61 ±1.05

3.60 ±0.99

4.50 ±1.36

17.23 ±1.7

0.95 ±1.5

0.62 ±0.7

20.57 ±3.9

M3

185 (1093, 23.7) 23.5

3.68 ±0.94

3.69 ±0.99

4.37 ±1.21

3.72 ±1.01

3.71 ±1.00

4.54 ±1.29

15.55 ±1.5

0.79 ±0.4

0.67 ±0.8

18.70 ±3.3

M4

162 (849, 20.7)

3.33 ±0.84

3.33 ±0.88

3.87 ±1.05

3.36 ±0.92

3.36 ±0.89

4.03 ±1.15

13.89 ±1.5

0.95 ±1.0

0.73 ±0.8

17.29 ±3.1

Group

Sen (%)

RV2 ±SE

hRV2 ±SE

24.7

hRV2.nss hRV2.nbs hRV2.nrs hRV2.ns Cost.nss Cost.nbs Cost.nrs ±SE ±SE ±SE ±SE ±SE ±SE ±SE

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Total cost ±SE

2.80 2.80 45.7 ±0.711 ±0.73

3.17 ±0.85

2.90 ±0.80

2.82 ±0.74

3.42 ±0.99

11.67 ±1.7

3.46 ±2.9

0.73 ±0.9

18.13 ±3.3

F2

27 (169, 3.5)

31.7

3.96 ±0.96

3.97 ±1.06

4.78 ±1.26

4.01 ±1.13

4.00 ±1.06

5.02 ±1.44

16.98 ±1.7

1.07 ±1.5

0.85 ±0.9

20.96 ±3.8

F3

204 (1212, 26.1) 24.0

4.07 ±0.86

4.07 ±0.98

4.82 ±1.18

4.11 ±1.00

4.11 ±0.98

5.04 ±1.25

15.44 ±1.6

0.89 ±0.6

0.91 ±1.0

19.20 ±3.3

F4

81 (476, 10.4)

28.4

3.65 ±0.78

3.66 ±0.88

4.25 ±1.04

3.70 ±0.94

3.70 ±0.88

4.46 ±1.15

13.87 ±1.6

1.08 ±1.3

0.98 ±1.1

17.94 ±3.2

F5+

47 (211, 6.0)

45.9

3.05 ±0.68

3.06 ±0.73

3.46 ±0.85

3.18 ±0.83

3.09 ±0.74

3.78 ±1.01

11.65 ±1.7

3.84 ±3.3

0.97 ±1.1

19.09 ±3.6

Accepted Article M5+

70 (313, 9.0)

Table 2. Model comparison to study effects of age (fitted as a smooth function), sex, recruitment age (RA), and their first-order interactions, on annual survival probability, annual breeding probability and annual reproductive success (i.e. the number of fledglings produced) in the common tern. The model with the lowest AIC for each dependent variable is indicated in bold, and parameter estimates for predictors in these models are reported in table A1.

Model

Survival

Breeding

Reproductive

probability

probability

success

df

AIC

df

AIC

df

AIC

3

3087.35

3

2113.57

3

2381.51

5

3079.61

5

2098.54

5

2198.69

Predictor

1.1

1

1.2

s(age)

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1.3

sex

1.4

RA

1.5

s(age) + sex

1.6

s(age) + RA

1.7

sex + RA

1.8

s(age) + sex + RA

1.9

s(age) * sex

1.10

s(age) * RA

1.11

sex * RA

1.12

s(age) * sex + RA

1.13

s(age) *RA + sex

1.14

s(age) + sex * RA

1.15

s(age) * sex * RA

4

3085.87

4

2112.00

4

2383.48

6

3091.95

6

2104.30

6

2385.08

6

3078.49

6

2098.88

6

2200.39

8

3085.23

8

2094.95

8

2194.36

7

3090.32

7

2105.00

7

2387.08

9

3083.76

9

2095.65

9

2196.33

8

3082.49

8

2102.67

8

2207.56

14

3090.59

14

2104.10

14

2219.14

10

3092.17

10

2110.50

10

2390.65

11

3087.76

11

2099.39

11

2203.47

15

3088.75

15

2104.73

15

2221.13

12

3085.38

12

2101.14

12

2200.29

18

3101.81

18

2124.21

18

2285.59

Figure legends Figure 1. Age-, sex- and recruitment age (RA)-specific annual survival probability, annual breeding probability, annual reproductive success (i.e. the number of fledglings produced) and reproductive value in the common tern, based on the models with the lowest AIC in table 2. Note that because RA groups did not differ in annual survival, their curves overlap, starting with the colour for young recruits, but overlapping in the colour for the oldest recruits at the ages they have in common.

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Figure 1

Survival probability

1.0

Breeding probability

1.0

Number of fledglings

Male

2.0

Reproductive value

Accepted Article

Figures

6

Female

(A)

1.0

RV: 2

3

4

0.9

0.9

0.8

0.8

0.7

0.7

0.6

0.6

1.0

(C)

0.9

0.9

0.8

0.8

0.7

0.7

0.6

0.6

2.0

(E)

1.5

1.5

1.0

1.0

0.5

0.5

0.0

0.0

6

(G)

5

5

4

4

3

3

2

2

1

1

0

0 5

10

15

20

(B)

5+

(D)

(F)

(H)

25

Age (yr)

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5

10

15

Age (yr)

20

25

Fitness prospects: effects of age, sex and recruitment age on reproductive value in a long-lived seabird.

Reproductive value is an integrated measure of survival and reproduction fundamental to understanding life-history evolution and population dynamics, ...
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