Early-life density-dependence effects on growth and survival in subantarctic fur seals

Transcription

1 DOI /s ORIGINAL ARTICLE Early-life density-dependence effects on growth and survival in subantarctic fur seals Nathan Pacoureau 1 Matthieu Authier 2 Karine Delord 1,2 Christophe Guinet 1 Christophe Barbraud 1 Received: 20 July 2016 / Accepted: 3 February 2017 / Published online: 21 March 2017 The Society of Population Ecology and Springer Japan 2017 Abstract Understanding the regulation of natural populations has been a long-standing research program in ecology. Current knowledge on marine mammals and seabirds is biased toward the adult component of populations and lacking are studies investigating the juvenile component. Our goal was to estimate demographic parameters on the pre-weaning stage of a subantarctic fur seal (Arctocephalus tropicalis) population on Amsterdam Island, suspected to be regulated by density-dependence. The influence of abundance on growth parameters (length and weight) and survival was assessed over a study period spanning 16 years. We evidenced a negative trend in population growth rate when density increased. Density-dependence models were favored for pup body size and mass growth. Abundance had a clear influence on body length at high population-density, pups grew slower and were smaller at weaning than pups born in years with low population density. Abundance partly explained pup body mass variation and a weak effect was detected on pre-weaning survival. The causal mechanisms may be increased competition for food resources between breeding females, leading to a reduction of maternal input to their pups. Our results suggested that pup favored survival over growth and the development of Electronic supplementary material The online version of this article (doi: /s ) contains supplementary material, which is available to authorized users. * Christophe Barbraud barbraud@cebc.cnrs.fr 1 2 Centre d Études Biologiques de Chizé, UMR CNRS 7372, Villiers en Bois, France Observatoire PELAGIS, Université de la Rochelle, UMS CNRS 3462, 4 allée de l Océan, La Rochelle, France their diving abilities in order to withstand the extreme fasting periods that are characteristic of this fur seal population. This analysis provides significant insight of densitydependent processes on early-life demographic parameters of a long lived and top-predator species, and more specifically on the pre-weaning stage with important consequences for our understanding of individual long-term fitness and population dynamics. Keywords Arctocephalus tropicalis Capture-markrecapture Growth model Marine top predator Population dynamics State space model Introduction A fundamental endeavour in population ecology is to identify the factors determining population abundance (May 1999). Among these, the role of density-dependence is still being debated. Its detection and the determination of its strength remain at the heart of current ecological and methodological issues (Berryman et al. 2002; Berryman 2004; Lebreton 2009; Herrando-Pérez et al. 2012). To better understand population dynamics, the effect of density on different age or stage classes should be quantified. Knowledge of density-dependence is also crucial to understand the impact of climate change on populations or in conservation biology (Hanski et al. 1996; Drake 2005). Densitydependence regulation of several large terrestrial mammal populations is well documented (Williams et al. 2013; and especially on large herbivores: see; Bonenfant et al. 2009). However, studies on density-dependence in marine mammals remain rather rare (Bonenfant et al. 2009; Williams et al. 2013). Vol.:( )

2 140 Popul Ecol (2017) 59: Marine mammals are top predators (sensu Sergio et al. 2014) widely accepted as keystone species because they can have disproportionate impacts on the structure and function of some marine ecosystems due to their large biomass and consumption of lower-trophic level preys (Bowen 1997; Sinclair 2003; Estes 2009; Estes et al. 2010). In addition, they are considered as indicators of environmental change (Jessup et al. 2004; Wells et al. 2004; Boyd et al. 2006; Moore 2008; Bossart 2011). Pinnipeds are amongst the most visible marine mammals given their large size and their onshore phase during breeding (Hindell et al. 2003). Depending on species, individuals can congregate together to form huge and compact breeding colonies which allows to investigate density-dependent relationships. Nevertheless, the role and the intensity of density-dependence in pinnipeds population regulation remain poorly known. Younger age classes of long-lived species constitute up to half of the total population and greatly contribute to the total reproductive value and demographic stochasticity (Sæther et al. 2013). Variations in vital rates of younger age classes could thus have long-term impacts on individual fitness and on the population dynamic and evolutionary processes (Gaillard et al. 2000; Sæther et al. 2013). Most demographic studies, particularly on marine mammals and seabirds, focused on life-history traits of the adult component of populations, but understanding early life demography is also required to obtain a panoptic view. The aim of our study was therefore to estimate early-life history traits and to test density-dependence effects on the pre-weaning stage of a marine top predator, the subantarctic fur seal (Arctocephalus tropicalis (Gray, 1872)) on Amsterdam Island, Indian Ocean. The fur seal population of Amsterdam Island has increased dramatically over the past decades (Guinet et al. 1994). Amsterdam Island is surrounded by subtropical relatively warm and low productivity waters (Gregg and Rousseaux 2014). One might expect density-dependent processes to occur, either through space limitation on coastal breeding sites and/or by increased competition for food resources at sea. Therefore, our specific objectives were to determine the influence of breeding population density on pre-weaning body-size and weight growth, and on pre-weaning survival. We tested for density-dependence in pup abundance time series data taking into account observation error (Lebreton 2009). Then we tested the following predictions regarding growth rate and pup survival parameters: 1. A decrease in birth size and weight when population density increases. The main reason would be a deterioration of dams body condition when population increases due to an increased competition for food. When competition increases the ability of a predator to forage is limited and food intake per capita decreases. 2. A decline in growth rates (snout-to-tail length and weight) of pups when population density increases. Due to high competition at sea, resources available for the dam may be limited and, by consequence, maternal inputs to pups before weaning. This constraint should be seen on pre-weaned pups because they are exclusively dependent of maternal input until weaning. 3. Finally, if pups are born smaller, lighter and have lower growth rates when density increases, their survival could be indirectly affected. We might also expect a decrease in pup survival due to trampling by adults as the population density increases on the breeding colonies. Materials and methods Study area and species Subantarctic fur seals were studied on Amsterdam Island, Indian Ocean ( S, E). The island (approximately 55 km²) is surrounded by subtropical, relatively warm (monthly average between 13 and 18 C), and low productivity waters (Gregg and Rousseaux 2014). The subantarctic fur seal is a long-lived and philopatric species. Females give birth to a single pup from late November to early January, with a mean parturition date in mid-december (Georges and Guinet 2000a). Dams alternate between foraging trips at sea, during which the pup fasts, and short lactation periods ashore. Lactating females undertake the longest recorded foraging trips (>30 days, > 1000 km from the colony) of any Otaridae (Beauplet et al. 2004). The pup rearing period lasts 10 months (Tollu 1974; Georges et al. 1999). Data Counts of newborn pups took place every year from 1994 to 2014 between 15 and 30 January on five distinct areas (areas 1, 2, 3, 31 and 32; Fig. 1) of the island. Three counts were carried out on each area the same day by three different persons, and if counts differed by more than 10% a fourth count was conducted. In this study, only counts from areas 1 and 2 were used to estimate pup abundance, since their boundaries were clearly and permanently defined over the whole study period. Due to logistic constraints counts could not be carried out every year in all areas. We thus used log-linear models and the software TRIM v3.52 (Pannekoek and van Strien 2001) to estimate total abundance of pups in these areas.

3 141 Fig. 1 The 49 areas defined by Roux (1986) on Amsterdam Island to survey subantarctic fur seals. Study areas are 1, 2, 3, 31 and 32 The number of pups in a given year is one component of population size and may depend on demographic factors such as the proportion of breeding females or the age structure. Therefore, a relationship between pup life history traits and the number of pups could be interpreted as density-dependence but could also be due to variations in demographic factors. However, given that no total population time series exist for this population and that female breeding probability, weaning probability and age structure were fairly constant during the study period in this population (Beauplet et al. 2005, 2006; Authier et al. 2011), we assumed that pup abundance depicted herein the total population size. During the study period, between 100 and 200 pups at the breeding colony of La Mare aux Éléphants on the north-east side of Amsterdam Island (Fig. 1, area 2) were temporarily identified within 12 h following their birth in December (Georges and Guinet 2000b) except in 1998 when fieldwork did not begin before January (Chambellant et al. 2003). Pups were sexed, weighed (±0.1 kg) and measured from snout to tail (±1 cm). At 1 month of age, marked pups were individually identified by permanent numbered plastic tags (Dalton Rototags, Dalton Supply, Nettlebed, UK) placed in connective tissue of the trailing edge of the fore flippers. Marked pups were longitudinally monitored until weaning (October) with two weighing and one size measurement by month. Additional daily weighing was conducted in May and June on a sub-sample of 30 pups each year. This longitudinal monitoring allowed estimating growth rates and survival of individual pups. Statistical analyses Density-dependent effects were investigated in pup annual abundance and in three life-history traits: pup growth (snout-to-tail length and weight) and survival from birth to weaning. Since pup growth and survival vary according to sex (Georges and Guinet 2000a, 2001; Guinet and Georges 2000; Beauplet et al. 2005), males and females were analysed separately. Some years (2002, 2004, 2008 and years before 1999) were removed from dataset used for analyses due to inadequate reliability and/or low sample sizes. Field protocols (counts, individual monitoring) could not be entirely fulfilled during those years due to logistical issues. We used a Bayesian approach to model growth parameters and abundance. In absence of independent information to specify informative priors, weakly informative priors were used: Student or normal distributions (Gelman 2006). Sensitivity analyses were conducted to check results robustness: a range of different prior distributions were tested (not shown). Three Markov chains were run for each model with different initial values. Out of a total number of

4 142 Popul Ecol (2017) 59: ,000 iterations, the first 30,000 were discarded ( warmup ), and one in five in the remaining 70,000 were selected for posterior inference. Thus, parameter posterior distributions were estimated from 42,000 values. Convergence of each parameter was checked with the Gelman and Rubin diagnostic (1992). Plots of fitted value vs residuals were checked to visually assess goodness-of-fit. Modeling population dynamics Pup abundance time series from 1999 to 2014 were analyzed using a discrete time stochastic Gompertz statespace model. This model allows to test density-dependence in time series and to estimate its intensity, whilst taking account of observation error (Lebreton and Gimenez 2013). Writing N t for true abundance in year t and x t = ln(n t ) the model is defined through the state process equation: x t+1 = r + (1 DD) x t + ε xt, where r is the logarithm of the multiplication rate (λ) when N = 1, DD is a constant parameter measuring the strength of density-dependence, and ε xt is a normally distributed process error with mean zero and process variance σ N ² (Lebreton and Gimenez 2013). We linked the logarithm of the observed counts (Y t ) with the logarithm of the true population size using the following equation: Y t = x t + ε Yt, where ε Yt is normally distributed observation error with mean zero and observation variance σ Y ². We used uniform priors for ε xt and ε Yt ( unif(0, 5)), and for parameter DD we used Student-t prior distribution with mean 0, degrees-offreedom parameter ν, and scale s ( t distribution(0, ν = 7, s = 1/ 0.001)), with ν and s chosen to provide minimal prior information (Gelman et al. 2008). Each chain was initiated by assuming a prior distribution on the initial state centred around the first observation of abundance, x 1 N(y 1, 0.01). Several authors (Delean et al. 2013; Lebreton and Gimenez 2013) recommended the choice of a reasonable prior for r based on external comparative information. We used the comparative demographic approach (Niel and Lebreton 2005) to estimate priors for r for subantarctic fur seals with the following formula: ( (s α s + α + 1) + ) (s s α α 1) 2 4 s α r ln 2, 2 α where s is the adult survival probability and α the mean age at first reproduction. Adult survival probabilities and age at first reproduction were taken from Beauplet et al. (2006) and Dabin et al. (2004), and were respectively between 0.9 and 0.95, and 5 and 8. The resulting prior distribution for r was N(0.077, 0.01). Modelling growth parameters We used a two-step methodology to study densitydependence on growth parameters. First, we fitted a density-independent growth model to length and weight measurements of pups by cohort. The second step consisted in adding density-dependent effects in different ways on these parameters and in selecting the most adequate model. Step 1: growth models Growth is continuous in pinnipeds, thus making asymmetric and non-linear functions more appropriate to model their growth (McLaren 1993). We chose the growth model developed by Jenss and Bayley (1937). It is a negatively accelerated exponential model with a linear asymptote. Growth is decomposed in two phases: an initial and exponential phase that gives way to a linear phase later in life. This linear growth can admit an asymptotic growth or not, depending on the data. Parameters were estimated from a mixed model (or hierarchical model). Our hierarchical model included a cohort effect (i) but no individual effect because some individuals had not sufficient growth data to permit including an individual effect. According to the Jenss-Bayley model, growth of a cohort i may be modelled with the following equation: l it = α 1i + α 2i t exp(α 3i + α 4i t) +ε it, (1) where the four parameters α ki are cohort specific growth parameters, t is the age and ε it is the residual error at age t (stochastic growth variability, measurement error ). Each parameter α ki can be decomposed: α ki = α 0 k + α1 ki, where α0 k are fixed effects common to all cohorts and α 1 are cohortspecific deviations (random effects), for k = 1,, 4. This ki model has a component for linear growth: α 1i + α 2i t where α 2i determines growth velocity. The other component is negative exponential: exp(α 3i + α 4i t) and models a progressive decrease of growth rate occurring quickly after birth. The Jenss-Bayley model was inappropriate for modelling weight of the extreme fasting behavior of pups (Verrier et al. 2011a). Therefore, we used an approach based on the difference in weight at a given age. Amsterdam Island fur seal pups reach their maximum weight in July around 230 days of age, and weight decreases beyond that date (Guinet and Georges 2000). A linear model was thus fitted over the period days: w it = α 5i + α 6i t. (2) It represented the global linear growth rate of pups between their second month of life and the moment of

5 their maximum weight. An early growth rate for the two first months of life of pup (0 60 days) was also estimated. Step 2: abundance effect on growth parameters Abundance effects on parameters of growth models were incorporated hierarchically. Each parameter was individually linked to abundance by a linear function: α ki = α 0 k + θ k N i + α 1 ki. (3) For length data modelled with the Jenss-Bayley model, we tested the effect of abundance (quantified by θ k ), obtained from the Gompertz state-space model, of the current year (N t ) and of abundance with a one year lag (N t 1 ) on the length at birth parameters (α 1i and α 3i ). Indeed, in pinnipeds, maternal characteristics, and hence environmental conditions encountered during gestation, have a significant influence on length at birth (Georges and Guinet 2000a, b, 2001). For weight, the effect of abundance of the current year and with a 1 year lag was tested with linear functions in a similar fashion to Eq. 3. One year lag density-dependent models tested the effect of density during gestation, which is the year before pup rearing. We used the Deviance Information Criterion (DIC; Spiegelhalter et al. 2002) for comparison between growth models, selecting the model with the lowest DIC. In practice, a difference in DIC values between five and ten is regarded as sufficient to select the model with the lowest DIC (Spiegelhalter et al. 2007). Analysis were performed using R Statistical Software v3.2.1 (R Core Team 2015) and via the interface from R ( rjags package; Plummer 2015) to JAGS ( Just Another Gibbs Sampler ; Plummer 2003). Estimates ± standard deviations are reported. Modelling pre weaning survival We used capture mark recapture (CMR; Lebreton et al. 1992) models to estimate survival probabilities. A monthly capture history was constructed for each individual from December to September. The few births (1% of individuals concerned) that occurred late November were shifted to December due to an insufficient number of individuals. Since individuals were found freshly dead on the breeding colony, survival histories combined live encounters and dead recoveries and we used multistate models (MSMR) (Pradel 2005) with two states: alive and dead. Capture histories were coded considering three events: 0 = not observed, 1 = seen alive, 2 = seen freshly dead. We started with model Φ month.coh p- month.coh d coh where probabilities of monthly survival Φ and capture p varied between months and cohorts (coh), and the monthly probability that a freshly dead individual was recovered d varied between cohorts. The parameter d 143 was constrained to be constant across months because the relatively small number of dead recoveries by month was insufficient to estimate d for each month and each cohort. Since the state freshly dead only appeared once in the capture histories, we could not use goodness-of-fit tests developed for multistate models (Pradel 2005). We thus assessed the fit of the Cormack Jolly Seber model using program U-CARE v (Choquet et al. 2009a). The global GOF test was built for males and females separately by adding each component of the GOF tests applied to each cohort separately. The CJS model fitted the data poorly (males: χ² = , df = 17, P < 0.001; females: χ² = , df = 15, P < 0.001). A closer inspection indicated that the lack of fit was largely due to heterogeneity in recapture probability (males: χ² = , df = 7, P < 0.001; females: χ² = , df = 7, P < 0.001). Individuals caught in month i were more likely to been caught in month i + 1 than individuals not caught in month i (trap-happiness). To account for trap-happiness, we considered two additional states: trap-aware which follows any occasion where an individual is captured, and trap-unaware which follows any occasion where it is not captured (Pradel and Sanz-Aguilar 2012). Transition probabilities between states were modelled with a twostep procedure where survival and trap-dependence were considered as successive steps in transition matrices. The fit of this new model, which explicitly accounted for a trap-dependence effect, was satisfactory (see Results ). From this initial constrained model, month and cohort effects were sequentially tested on each parameter starting with d, then p and finally on survival. Model selection was performed with a modified version of the AIC corrected for small sample sizes (AIC c ; Akaike 1974). Two models we considered to differ when the AIC c difference was greater than 2 (ΔAIC c > 2; Burnham and Anderson 2002:70). We then tested if variation in pup survival or capture could be best modelled with linear or quadratic (on a logit scale) trends by cohort or by month. Trends with varying slopes and intercepts by cohorts were tested. An ANODEV test (Skalski et al. 1993) was used to detect these trends and the proportion of deviance taking into account (R²) was also calculated (Grosbois et al. 2008). Once the best structure was selected for each parameter, corrected abundance obtained with the Gompertz state-space model was included as a covariate in interaction with survival of each cohort and the R² was calculated. All estimates and AIC c values were computed using program E-Surge v1.9.0 (Choquet et al. 2009b). Because MSMR models are prone to local minima during the likelihood maximisation routine, we ran the same models with random initial values at least 10 times to ensure that they converged to the lowest deviance.

6 144 Popul Ecol (2017) 59: Results Population dynamics Pup abundance increased between 1999 and 2014 (Fig. 2) from 1800 to 2600 individuals. This corresponded to a mean annual population growth rate of (+2.5% per year). Population growth rate (λ) tended to decrease between 1999 and The relationship between population growth rate and abundance suggested that, when the pup population exceeded 2400 individuals, growth rate fell below 1 (Fig. 3). However, the Gompertz state space model indicated that the posterior probability that density-dependence was constraining population growth (Pr (DD > 0)) was only 0.76 (95% credibility interval for parameterdd: to ). Although not definitive, this result was suggestive of density-dependence. Body length There was no significant trend in length at birth over the study period (Fig. 4). Growth model selection for length is shown in Table 1. Models with density-dependence were favoured for both sexes. The best models included an effect of abundance the current year or with a 1 year lag on growth parameters. Sensitivity analyses and examination of residuals suggested a good fit and robustness to prior choice (not shown). Growth parameter estimates for body length of male and female pups based on a model with constant parameters are shown in Table 2. There was a significant sex difference in parameter α 0. This parameter was greater for males 1 (82.6 ± 0.9) than females (79.7 ± 0.8) (z = 2.406, P = 0.008). Others parameters did not differ significantly between sexes (all P s > 0.359). Thus, males were longer at birth than females but grew at the same rate. Density-dependence parameters are shown in Table 3 for the model with the lowest DIC for males and females. 95% Credibility intervals of parameter Ɵ 1 and Ɵ 3 didn t include 0 in both sexes, which meant that parameters α 1i and α 3i were strongly influenced by abundance during the previous year. Parameter α 2i appeared to be unrelated to abundance (95% credibility intervals of Ɵ 2 included 0). Parameter α 4i was influenced significantly by abundance of the previous year for both sexes, and by abundance of the current year for males (95% Credibility intervals of Ɵ 4 didn t include 0). Results nevertheless evidenced a negative effect of current year abundance on α 4i for females (92% of values of Ɵ 4 were smaller than 0). Predicted growth curves for male and female pup length from the selected model [with density-dependence; see residuals in Fig. S1 in Electronic Supplementary Material (ESM)] showed no abundance effect on length at birth but a strong effect on growth (Fig. 5), suggesting that pup size at weaning was lower at high density than at low density. Fig. 2 Observed (empty circle) and corrected (solid circle) abundance of pups on areas 1 and 2 from 1999 to 2014 obtained from a Gompertz state-space model. Error bars are standard errors

7 145 Fig. 3 Population growth rate (λ= N t+1 /N t where N t+1 is population size at time t + 1) of pups in relation to abundance at year t. Error bars are 95% confidence intervals Fig. 4 Body size at birth for newborn females (solid circle) and males (empty square) subantarctic fur seal of La Mare Aux Éléphants from 1999 to Numbers are sample sizes for both sexes. Error bars are standard deviations Body weight Over the study period, there was no trend in the maximum weight of male pups (Fig. 6), but female pups maximal weight decreased (slope estimate = 0.14, P = 0.04, R² = 0.28). Males were heavier than females at birth (z > 5, P < 0.001), and grew faster than females during their first 2 months (z = 2.45, P = 0.007) (Table 4) and between 30 and 230 days (z > 5.22, P < 0.001) (Table 5). Model selection for growth during the two first months of life and between 30 and 230 days, indicated that density-dependent models

8 146 Popul Ecol (2017) 59: Table 1 Modelling the effect of abundance on body length from birth to weaning of male and female pup of subantarctic fur seals from Amsterdam Island Model DIC ΔDIC Penalty Mean deviance N Ind (623) N Obs (4058) N Ind (800) N Obs (5418) DD model (linear effect of N 1 on α 1 and α 3 ; N on α 2 and α 4 ) ,862 DD model (linear effect of N 1 on all α k ) ,862 DD model (linear effect of N on all α k ) ,864 Model without DD (fixed α for all years) ,037 DD model (linear effect of N 1 on all α k ) ,315 DD model (linear effect of N 1 on α 1 and α 3 ; N on α 2 and α 4 ) ,316 DD model (linear effect of N on all α k ) ,324 Model without DD (fixed α for all years) ,790 The number of individuals and observations are indicated in brackets for each sex N Ind is the number of individuals N Obs is the number of observations Table 2 Growth parameter estimates for body length of male and female pups based on a model with constant parameters Parameter Mean Standard deviation Male Female Male Female α α α α Growth rate of females between 30 and 230 days were strongly affected by abundance of the previous year (98% of values of Ɵ 6 were smaller than 0), suggesting that females were lighter at 230 days at high density than at low density. The same trend was observed for males with 91% of values of Ɵ 6 smaller than 0. In females, but not in males, growth rate from birth to weaning was strongly influenced by abundance of the previous year (90% of values of Ɵ 6 were smaller than 0). Table 3 Percentage of negative values in the posterior distribution of density-dependence parameters (Ɵ) for body length Male Female DD model (linear effect of N 1 on α 1 and α 3 ; N on α 2 and α 4 ) Ɵ Ɵ Ɵ Ɵ DD model (linear effect of N 1 on all α) Ɵ Ɵ Ɵ Ɵ Values shown in bold indicate parameters for which 95% credible intervals do not include zero were preferred for both sexes (Tables 6, 7, respectively). Sensitivity analyses and examination of residuals suggested a good fit and robustness to prior choice (not shown). Density-dependence parameters are shown in Table 8 for models with the lowest DIC for males and females. α 5i (weight at birth) of growth model between 0 and 60 days seemed to be unrelated to abundance for both sexes. Pre weaning survival Goodness-of-fit tests of the MSMR model taking into account trap-dependence for males indicated a good fit (χ² = 11.68, df = 10, P = 0.31). Dead recovery probability varied according to cohorts. Capture probability increased for trap-aware individuals and decreased for others (Fig. 7a) in all cohorts. Survival increased quadratically by month and differently according to cohorts (Table 9; Fig. 7b). For females, goodness-of-fit tests of the MSMR model taking into account trap-dependence indicated a good fit (χ² = 11.26, df = 8, P = 0.19). Dead recovery probability varied according to cohorts. Capture probability increased for trap-aware individuals and decreased for others (Fig. 8a) in all cohorts. Survival tended to increase quadratically by month and differently according to cohorts (Table 10; Fig. 8b). Models with density-dependence were not selected with AIC c compared to the models where survival varied quadratically by month and specifically by cohort, but had lower AIC c values that models with the same monthly quadratic survival trend for all cohorts (Tables 9, 10). However, slope parameters for models where pup survival was a function of density were all statistically significant (Table 11), although the proportion of variance explained was low (Tables 9, 10). Slope

9 147 Fig. 5 Theoretical growth curve for male (black) and female (grey) at low density (1800 pups; solid lines) and at high density (2600 pups: dashed lines) based on density-dependent model (linear effect of N 1 on all parameters α). The unit for age is days Fig. 6 Maximum weight reached at 230 days (±15 days) for females (solid circle) and males (empty square) subantarctic fur seal of La Mare Aux Éléphants from 1999 to Numbers are sample sizes for both sexes. Error bars are standard deviations Table 4 Growth parameter estimates for weight of male and female pups from birth to 60 days based on a model with constant parameters Parameter Mean Standard deviation Male Female Male Female α α Table 5 Growth parameter estimates for weight of male and female pups from 30 to 230 days based on a model with constant parameters Parameter Mean Standard deviation Male Female Male Female α α

10 148 Popul Ecol (2017) 59: Table 6 Modelling the effect of abundance on weight variation from birth to 60 days of male and female pup of subantarctic fur seals from Amsterdam Island N Ind (618) N Obs (2828) N Ind (795) N Obs (3691) Models DIC ΔDIC Penalty Mean Deviance DD model (linear effect of N on all α k ) DD model (linear effect of N 1 on all α k ) Model without DD (fixed α for all years) DD model (linear effect of N on all α k ) ,332 DD model (linear effect of N 1 on all α k ) ,332 Model without DD (fixed α for all years) ,592 The number of individuals and observations are indicated in brackets for each sex Table 7 Modelling the effect of abundance on weight variation from 30 to 230 days of male and female pup of subantarctic fur seals from Amsterdam Island N Ind (477) N Obs (11,506) N Ind (639) N Obs (15,400) Models DIC ΔDIC Penalty Mean Deviance DD model (linear effect of N on all α k ) ,232 DD model (linear effect of N 1 on all α k ) ,232 Model without DD (fixed α for all years) ,148 DD model (linear effect of N 1 on all α k ) ,385 DD model (linear effect of N on all α k ) ,386 Model without DD (fixed α for all years) ,459 The number of individuals and observations are indicated in brackets for each sex Table 8 Percentage of negative values in the posterior distribution of density-dependence parameters (Ɵ) for weight Male A value shown in bold indicates a parameter for which 95% credible intervals does not include zero parameters suggested a negative effect of abundance on survival for both sexes. Estimated pup s annual survival between 1999 and 2014 are shown in Fig. 9. Males tended to have a lower survival probability (mean ± SE 0.53 ± 0.05) than females (mean ± SE 0.58 ± 0.04). For both sexes, excluding the poor survival observed in 1999, there was a negative trend for survival from 2000 to Discussion Female 0 60 day day 0 60 day day DD model (linear effect of N on all α k ) Ɵ Ɵ DD model (linear effect of N-1 on all α k ) Ɵ Ɵ As population size increases in large mammals, densitydependent processes are enhanced and lead to a reduction in population growth rate (Sinclair 2003; Sibly et al. 2005; Bonenfant et al. 2009). In subantarctic fur seals on Amsterdam Island, our analysis of pup abundance time series from 1999 to 2014 suggests that density-dependent processes occur in this population. We clearly showed a negative influence of abundance on length and weight growth rates of pups. Pup survival between birth and weaning seem also related to abundance, but with a relatively weak influence. Additionally, our results support conclusions of several studies on subantarctic fur seals or other Otaridae that males are heavier at birth than females (Trillmich 1986; Georges and Guinet 2000a; Chilvers et al. 2007; Oosthuizen et al. 2015). However, we found a between-sex difference in weight growth rate, which was not detected previously in this population (Guinet and Georges 2000; Chambellant et al. 2003; but see; Luque et al. 2007; Oosthuizen et al. 2015). Pup abundance Previous studies on this subantarctic fur seal population suspected, but did not evidence, density-dependent processes to occur (Chambellant et al. 2003; Dabin et al. 2004; Beauplet 2005; Authier et al. 2011). The parameter DD quantifying density-dependence suggested that the population growth rate decreased when the population increased. Even if our modeling approach (state-space model) allowed to separate observation error and inherent stochastic noise in the time series (Lebreton 2009; Knape and De; Valpine 2012), count precision (estimated error of 12% by the Gompertz model) may not be sufficient to statistically detect a density-dependent effect. In addition,

11 a b Fig. 7 a Capture probability variation for trap-aware individuals (empty circle) and trap-unaware individuals (solid circle) for males pups. b Survival probability variation for males pups in Error bars are 95% confidence intervals although we assumed that the number of pups depicted the total population size based on the relative temporal stability of female breeding probability and age structure (see Materials and methods ), the number of pups make a relatively small percentage of the whole population on Amsterdam Island. Pup growth Contrary to our first prediction, no effect of abundance was found on birth length and weight. One hypothesis that 149 might explain this result is that subantarctic fur seal females in poor condition could delay or terminate their reproduction instead of giving birth to a smaller pup. Indeed, pinnipeds may adjust the amount of energy allocated to the foetus (Bowen et al. 2002). Embryonic diapause occurs in fur seals (Bester 1995), during which embryo s growth is stabilized for about 4 months in subantarctic fur seals. Dams must ensure simultaneously the growth of the embryo and the rearing of its pup from April to December. Prey availability for dams is thus a major limiting factor for foetus growth and extended foraging trips of breeding females at Amsterdam Island (11 23 days in comparison of 1 12 days for other species: Boyd 1999; Georges and Guinet 2000b; Beauplet et al. 2004; Staniland et al. 2010) suggest that per capita prey availability is relatively low (Beauplet et al. 2004). It was shown in a fur seal species with an analogous lactation period that females in poor body condition were less likely to give birth the following year (Guinet et al. 1998). These authors reported higher abortion rates and lower implantation rates when dam body condition was poor. Another non-exclusive hypothesis could be that during the last 3 months of gestation, when most of prenatal pups growth is taking place, no or little density-dependence occurs on the foraging areas. During this period after their pup is weaned and 3 month prior to parturition, females are able to extend their foraging range over large areas resulting in an intrasexual competition between females which may be reduced as individuals are spread over a much larger foraging area compared to the pup rearing period. Females can also reside in high prey density areas, without having to commute back and forth to their breeding location. We found that body growth rate of pups was influenced by pup abundance of the previous and the current year, verifying our second prediction. In pinnipeds, especially in fur seals, pup growth rate during rearing reflects the level of maternal input because pups are entirely dependent of their mothers for nutrition (Trillmich 1996; Guinet and Georges 2000; Guinet et al. 2000; Bowen et al. 2002; Verrier et al. 2011a; Gentry and Kooyman 2014). Thus, we suspect that when population size increased, intraspecific and specifically intrasexual competition between lactating adult females also increased in this oceanographic context of impoverished prey availability (Gregg and Rousseaux 2014), leading to reduced maternal input to pups and thus limiting pup growth. In this case density, expressed as the number of females per km² of foraging habitat, would affect foraging performances of breeding females and consequently pup growth. Alternatively, but not exclusively, the reduction in pup growth could be due to negative effects of density onshore. For example, high numbers of females and pups per m² on the breeding colony may facilitate dispersion of diseases

12 150 Popul Ecol (2017) 59: Table 9 Modelling capture (p) and survival (Φ) probabilities for young males between birth and weaning Model Hypothesis tested AIC c ΔAIC c k Dev ANODEV P R² Modelling capture probabilities Φ month*coh [ ]d coh p month+coh Monthly variation by cohort (additive effect) p coh_linear Linear trend between cohorts (27,14) p month*coh_quadratic Cohort specific monthly quadratic trend (77,156) < p coh_quadratic Quadratic trend between cohorts (29,12) p month*coh_linear Cohort specific monthly linear trend (51,182) p coh Varying by cohort p month Varying by month p month_linear Monthly linear trend (3,14) p month_quadratic Monthly quadratic trend (5,12) p Constant p month*coh Varying by cohort and by month Modelling survival probabilities [ ]p month_linear d coh Φ month*coh_ quadratic Cohort specific monthly quadratic trend (38,78) < Φ month*coh_linear Cohort specific monthly linear trend (25,91) Φ month+coh Monthly variation by cohort (additive effect) Φ coh_quadratic Quadratic trend between cohorts (14,16) Φ coh_ linear Linear trend between cohorts (13,7) Φ month Varying by month Φ coh Varying by cohort Φ month_ quadratic Monthly quadratic trend (2,6) Φ month_ linear Monthly linear trend (1,7) Φ Constant Modelling density-dependence on survival [ ]p coh*month_quadratic d coh Φ month*coh_ quadratic.n.n² Quadratic density-dependence Φ month*coh_ quadratic.n Linear density-dependence Trends were tested with an analysis of deviance (ANODEV). ANODEV is the F-statistic (F (df1,df2) ), R² is the proportion of variance taking into account by the trend. Selected models are indicated in bold AIC c Akaike s information criterion corrected for small sample size, ΔAIC c AIC c difference between the model and the best model, k number of parameters estimated, Dev Deviance and more aggressive behavior of other breeding females or males towards conspecific or pups, thereby leading to nonlethal infection or mother pup separations (Harcourt 1992; Cassini 1999; Chilvers et al. 2005). The effect of abundance of the previous year on pup growth rates could be also due to carry-over effects of density during gestation. However, we were not able to unravel delayed and direct effects in our study. The deterioration of growth performance due to densitydependent processes, combined with the extreme repeated fasting durations that pups have to face, result in the lowest growth rate from birth to weaning ever observed among Otaridae (see Chambellant et al. 2003; Beauplet 2005). Growth rates at Amsterdam Island seemed most likely to be the lowest growth rates among Otaridae, even lower than at Marion island or Gough island (Oosthuizen et al. 2015). We could not fit the Jenss-Bayley growth curve models to pup weight data. Linear models accounting for an effect of abundance were favoured. Weight growth rate parameters from 30 to 230 days were influenced by abundance with a stronger effect on female pups than male. Hence, if we assume that, as for body length growth, density-dependent effects translate into lower maternal input during years with high density, the same impact might appear on weight growth rate. This effect of abundance on pup weight growth was also apparent, although not as strong, for growth rates from birth to 60 days growth. Pup survival Our results suggest a weak negative effect of abundance on pre-weaning pup survival for both sexes. We suggest two non-exclusive alternative hypotheses to explain this weak effect of abundance on pre-weaning survival. First, as suggested by Georges and Guinet (2000a), the topology of La Mare aux Éléphants (large boulders and blocks of rock)

13 a b 151 (Beauplet et al. 2003; Guinet et al. 2005; Verrier et al. 2011b). Amsterdam Island pups seem to favor energy sparing, in order to survive to the increasing fasting duration during lactation, over swimming abilities (Beauplet et al. 2003; Verrier 2007), making density-dependent effect more visible for growth than for survival. Indeed, young of the year do not spend much time in water developing their abilities but rest on land (Arnould et al. 2003; Guinet et al. 2005; Verrier 2007; Verrier et al. 2009, 2011b). Nevertheless, this trade-off potentially makes pups vulnerable to environmental conditions once they become independent and leave the colony. In many mammal species including fur seals, large size and heavy weight at weaning are positively related to post-weaning survival (Festa-Bianchet et al. 1997; Beauplet et al. 2005; Gastebois et al. 2011; Verrier et al. 2011a). In fur seals, this relationship is probably linked to foraging capacities, since Guinet et al. (2005) found changes in diving performance related only to pup size and not to its age. Since density-dependence reduces pup growth and weaning condition, increasing abundance is expected to have a strong negative effect on post-weaning juvenile survival. Bonenfant et al. (2009) showed that density-dependent effects are generally not found on survival from birth to weaning in large vertebrate herbivores giving birth at one offspring annually, compared to species with several offspring (that have a higher energy expenditure per breeding attempt), or post-weaning survival (e.g., Clutton- Brock et al. 1987). Possible joint density independence influence Fig. 8 a Capture probability variation for trap-aware individuals (empty circle) and trap-unaware individuals (solid circle) for females pups. b Survival probability variation for females pups. Error bars are 95% confidence intervals offers many hiding places where pups can avoid a densitydependent mortality due to trampling by adult males (Harcourt 1992). Therefore, such an effect of density, expressed as the number of females per m² in the breeding colony, seems unlikely. Second, pre-weaning survival may be favoured at the expense of body and weight growth when abundance increases. There is a strong trade-off between growth and survival in pinnipeds (Trillmich 1996), and the extreme fasting endured by pups may exacerbate this trade-off. During the rearing, pups must both manage their fat reserves and develop their swimming and diving abilities Environmental factors such as oceanographic conditions on the foraging areas were not taken into account herein due to a lack of accurate knowledge on at-sea population distribution and thus on oceanographic factors that could potentially affect foraging efficiency. Although our study investigated and evidenced density-dependence processes in early-life demographic traits, extrinsic factors, potentially interacting with density-dependent effects, may contribute to population dynamics. The negative trend in yearly pre-weaning survival of pups could be due to trends in environmental factors such as oceanic productivity, competition with other meso-predators at sea, or direct predation on subantarctic fur seals at sea. Conclusion Compared to terrestrial mammals (Bonenfant et al. 2009; Williams et al. 2013), relatively few studies investigated

14 152 Popul Ecol (2017) 59: Table 10 Modelling capture (p) and survival (Φ) probabilities for young females between birth and weaning Model Hypothesis tested AIC c ΔAIC c k Dev ANODEV P R² Modelling capture probabilities Φ month*coh [ ]d coh p month+coh Monthly variation by cohort (additive effect) p month*coh_linear Cohort specific monthly linear trend (51,182) p coh_quadratic Quadratic trend between cohorts (29,12) p coh_linear Linear trend between cohorts (27,14) p month*coh_quadratic Cohort specific monthly quadratic trend (77,156) p coh Varying by cohort p month_quadratic Monthly quadratic trend (5,12) p month_linear Monthly linear trend (3,14) p month Varying by month p month*coh Varying by cohort and by month p Constant Modelling survival probabilities [ ]p month_ quadratic d coh Φ month*coh_quadratic Cohort specific monthly quadratic trend (38,78) < Φ month+coh Monthly variation by cohort (additive effect) Φ month*coh_linear Cohort specific monthly linear trend (25,91) Φ month Varying by month Φ coh_quadratic Quadratic trend between cohorts (14,6) Φ coh_linear Linear trend between cohorts (13,7) Φ month_quadratic Monthly quadratic trend (2,6) Φ month_linear Monthly linear trend (1,7) Φ coh Varying by cohort Φ Constant Modelling density-dependence on survival [ ]p month_ quadratic d coh Φ month*coh_quadratic.n Linear density-dependence Φ month*coh_quadratic.n.n² Quadratic density-dependence Trends were tested with an analysis of deviance (ANODEV). ANODEV is the F-statistic (F (df1,df2) ), R² is the proportion of variance taking into account by the trend. Selected models are indicated in bold AIC c Akaike s information criterion corrected for small sample size, ΔAIC c AIC c difference between the model and the best model, k number of parameters estimated, Dev Deviance the effects of density-dependence in marine mammals (Eberhardt 1977, 2002; Rotella et al. 2009; Ferrari et al. 2013; Williams et al. 2013). Pinnipeds are good model species to investigate density-dependence in large marine Table 11 Values of beta parameter for density-dependent parameter slope in the model with quadratic density-dependence in survival for males and linear density-dependence in survival for females. Mean estimate (95% confidence intervals) are reported Interaction with linear parameter of survival Interaction with quadratic parameter of survival Quadratic density-dependent model for male β N 28.7 (20.0; 37.4) 35.7 ( 45.7; 25.8) β N² 27.5 ( 36.2; 18.8) 34.3 (24.5; 44.2) Linear density-dependent model for female β N 1.1 (0.5; 1.8) 1.2 ( 2.0; 0.4) mammals and long-lived species. Results obtained here are consistent with the existing literature on large terrestrial mammals. We found that early-life demographic traits were related to breeding population abundance. We clearly evidenced a deterioration in pup growth and body condition at weaning when breeding population increased. A strong intraspecific competition between lactating adult females, exacerbated by low productivity of foraging habitat, was suspected to occur when population size increased and lowered maternal input to pups, thus limited their growth. Body condition is generally connected with survival and it appeared herein a strong trade-off in favour of survival. Pup pre-weaning condition may be more sensitive to stressful conditions than preweaning survival, and may respond to increasing density before pre-weaning survival. Given how female body length is a critical determinant of reproductive success under selection (Beauplet and