# Individual variability in the phenology of an asynchronous penguin species induces consequences on breeding and carry-over effects

Nicolas Joly, Andre Chiaradia, Jean-Yves Georges, Claire Saraux

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Nicolas Joly, Andre Chiaradia, Jean-Yves Georges, Claire Saraux. Individual variability in the phenology of an asynchronous penguin species induces consequences on breeding and carry-over effects. Oecologia, 2025, 207 (1), pp.16. 10.1007/s00442-024-05644-6. hal-05411281

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1 Running head: Phenology and breeding behaviour

2 Individual variability in the phenology of an asynchronous penguin species induces

3 consequences on breeding and carry-over effects.

4 NICOLAS JOLY¹*, ANDRE CHIARADIA², JEAN-YVES GEORGES¹, CLAIRE SARAUX¹

5

6 ¹Université de Strasbourg, CNRS, Institut Pluridisciplinaire Hubert Curien (IPHC), UMR

7 7178, 23 rue Becquerel, F-67000 Strasbourg, France

8 ² Conservation Department, Phillip Island Nature Parks, PO Box 97, Cowes, VIC 3922,

9 Australia

10 *Email: nicolas.j973@gmail.com

11

12 Author Contributions: AC and CS conceived the ideas, designed methodology and collected

13 the data; NJ and CS analyzed the data NJ led the writing of the manuscript. All authors

14 contributed critically to the drafts and gave final approval for publication. Other authors

15 provided editorial advice.
16

17 **<u>Abstract</u>**

18 Phenology is a major component of animals' breeding, as they need to adjust their breeding
19 timing to match optimal environmental conditions. While the effects of shifting phenology are
20 well-studied on populations, few studies emphasise its ecological causes and consequences at
21 the inter-individual level. Using a 20-year monitoring of more than 2500 breeding events
22 from ~500 breeding little penguins (*Eudyptula minor*), a very asynchronously breeding
23 seabird, we investigated the consequences of late breeding on present and next breeding
24 events. We found that individuals breeding later had reduced breeding success, lighter chicks
25 at fledging, lower probability of laying a second clutch, and decreased parents' post-breeding
26 body condition. Importantly, we found important cycling effects where delayed breeding
27 during a given year led to significantly later laying date, lower breeding probability and lower
28 breeding success when they breed during the next season, suggesting potential carry-over
29 effects from one season to the next. To further understand the causes of such variability in
30 phenology while earlier breeding is associated with better individual fitness, we aimed to
31 assess intrinsic differences among individuals. We showed that the heterogeneity in breeding
32 timing was partly fixed, the laying date being a significantly repeatable behaviour (17%),
33 asking for more studies on heritability or early-development effects. This extensivestudy
34 highlights the combined roles of carry-over effects and intrinsic differences on individual
35 phenology, with important implications on breeding capacity through life.

36 **Key words: Breeding timing, early-life, repeatability, life-history, fitness**
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## Introduction

The link between animal phenology and breeding outputs is driven by many processes such as changes in abiotic conditions or competition (e.g. Samplonius & Both 2019), although many studies pointed out the major role of the variability in the amount of energy available in the environment through match/mismatch with food resources (Durant et al. 2007, Hipfner 2008, Regular et al. 2014). These potential mismatches are themselves driven by variations in the environment (Grémillet and Boulinier 2009). Phenology is a particularly responsive trait to environment variability (Visser et al. 2004, Reed et al. 2009) and trends such as the ones recently observed with climate change (Parmesan and Yohe 2003, Poloczanska et al. 2013, Cohen et al. 2018)

While the effects of phenology at the population level are well described, very few studies emphasise its importance in terms of inter-individual variability on animal breeding cycle. Yet, inter-individual variability is known to be a crucial ecological driver of breeding success and fitness (Gordo et al. 2013, Gilsenan et al. 2020, Joly et al. 2023). It consists of a combination of differences in individual plasticity (i.e strength of individual response to environmental variations) and individual repeatability (i.e consistent behaviour across time) (Reed et al. 2009, Dingemanse et al. 2010, Lourenço et al. 2015, Gilsenan et al. 2020). Individual capacity to cope with shifts in environmental conditions is not uniform, which leads to important differences in the breeding timing among individuals of the same population (Reed et al. 2009). Further, traits such as breeding timing are also expected to be partly consistent during individual life, which might be explained by heritability (Stirling et al. 2002) or conditions experienced during development and growth (Lindström 1999, Monaghan 2007).

Inter-individual variability in phenology thus implies that some individuals will better match the optimum environmental conditions (e.g. prey availability) than others in a given year. In
long-lived species such as seabirds, individuals tend to favour their own survival and maintenance over offspring when facing unfavourable environmental conditions to maximise future breeding events (Goodman, 1974; Stearns, 1992). Thus, phenological mismatch with prey availability should directly affect individual breeding output through detrimental breeding decisions favouring adult survival over offspring's (e.g. nest desertion or reduced clutch size; Stearns 1989, Chastel et al. 1995) or through less energy allocated to offspring development (Watanuki et al. 2009). Still, life-history strategies also vary within a population among individuals, so that even in long-lived species, some individuals may avoid these reduced breeding outputs by allocating significant amounts of energy to offspring, in which case they may face post-breeding exhaustion (Shultz et al. 2009). In this case, carry-over effects may occur from one breeding season to the next (Harrison et al. 2013). For instance, individuals may take more time and have a slower recovery, potentially affecting their future breeding events (Harrison et al. 2011).

Here we focused on the breeding phenology of little penguin (*Eudyptula minor*) in the world's largest colony of this species, at Phillip Island, Australia. Little penguin phenology is especially interesting because of their particularly asynchronous breeding timing (4 to 6 months between earliest and latest birds; Reilly and Cullen 1981). Their breeding cycle also allows them to regularly attempt more than one breeding event per season (Reilly and Cullen 1981), further increasing the breeding season duration range. In addition to being asynchronous, this colony of little penguins exhibited a quick and strong shift towards earlier breeding timing (around one month) during the last decades (Cullen et al. 2009), due to changes in marine conditions and prey distribution in the area (Ridgway 2007, Last et al. 2011). Such important variations in little penguin phenology have been recently shown to largely explain little penguin foraging success at the population scale (Joly et al 2022) as well as individual lifetime fitness (Joly et al. 2023).
Using a long-term monitoring of around 2500 breeding events from more than 500 penguins across 20 years, we first assessed whether the variability in phenology resulted from fixed differences among individuals or individual plasticity by testing how repeatable breeding timing was among individuals. While little penguin phenology changes importantly from year to year as a response to the environment (Joly et al. 2022). Once the year effect is removed, we still expected part of the variability in laying to be repeatable, with some birds breeding consistently earlier than others.

Second, we aimed to understand the paths through which delayed phenology affects penguin reproduction. As an increased delay is thought to increase the mismatch with prey (Reed et al. 2009), thus inducing poorer foraging (Joly et al. 2022), we expected later breeding to be associated with lighter and slower chick growth and deteriorated breeding outputs (e.g. breeding success, number of breeding events). We expected delayed breeding adults to invest less energy in parental care (e.g., shorter guard period) associated with lower breeding success (Chiaradia and Kerry 1999), smaller chicks at fledging and fewer second clutches attempted to not lose weight during breeding.

Finally, we investigated the carry-over effects of late breeding and the consequences of a poor breeding season on the performances in the subsequent year. We expected that late breeding would induce poor post-breeding conditions (Salton et al. 2015, Fayet et al. 2016) that would themselves delay the next breeding event, creating a cycle in which phenology would constantly delay. Regarding demography, late breeding (and associated poor post-breeding conditions) should decrease the likelihood of breeding during the next breeding event. Penguins that still attempted breeding should display lower breeding success (Shoji et al. 2015) and lower probability of trying a second clutch. However, skipping a breeding event (i.e. skipping breeding season or not attempting a second clutch) might help break the
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negative cycle by allowing a better post-breeding recovery, inducing an earlier breeding the
following year (Shoji et al. 2015).

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## Methods

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### 1. Little penguins monitoring

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The studied colony is located in the Summerland Peninsula on Phillip Island (38°15' S, 143°30' E), Victoria, Australia, consisting of 28,000 to 32,000 breeding adults (Sutherland and Dann 2012). This study spans 20 consecutive breeding years (from 2001 to 2020). As little penguin breeding season occurs during the austral spring and summer (September to March), a breeding year refers to austral spring, e.g. 2001 corresponds to the breeding season 2001-2002. Overall, the little penguins' breeding season comprises a short courtship period, quickly followed by laying two eggs. Parents alternate incubation of the eggs for 35 days.

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After hatching, the parents take intensive care of the chicks (guard period) for a period usually lasting from one week to one month, during which the two parents alternate daily between staying ashore with the chicks and foraging at sea. After this guard period starts the post-guard (~40 days) when the parents leave the chicks alone ashore and go to forage at sea both at the same time for trips that can extend from 1-2 days (most common) to more than 10 days.

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Penguins monitored for this study (516 in total, 115 ± 15 per year in average) had been previously implanted with 23 mm ISO HDX transponder (Allflex, Australia) between the shoulder blades (Chiaradia & Kerry 1999) as chicks or when first encountered in the colony and nested in a site containing approximately 100 artificial burrows (wooden nest boxes). Sex (equal distribution in our case) was assessed using bill measurement (Arnould et al. 2004) and confirmed by pair behaviour. Individual hatching season (thus age, 8.3 ± 4.5 years in our case) was either known due to their marking as chicks or estimated when marked as adults, assuming they were three years old (average age at maturity) when first seen breeding in the

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colony. Nests were monitored three times a week to assess breeding pairs, laying and hatching dates and the number of eggs, chicks and fledglings. Chick mass was also weighed three times a week during post-guard (i.e. starting the first day, chicks were left alone in the nest to avoid creating too much disturbance).

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Nest monitoring was complemented by an Automated Penguin Monitoring System (APMS) located on the main passage used by the penguins between the colony and the sea – see details in Chiaradia and Kerry (1999). This APMS records ID and body mass of individual penguins going in or out of the colony. Only body masses ranging from 700 to 1700g were considered valid (see Salton et al. 2015 and Saraux & Chiaradia 2021). The second entry point to the colony was only equipped with a transponder reader used to detect individual ID but no mass (26% of the detections during the breeding period).

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## 2. Little penguins breeding traits

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### 2.1 Breeding events

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A penguin breeding event was considered as soon as an egg was laid in the nest. Penguin breeding timing was defined as the date of egg laying. The laying date reflects both the population variability in phenology across breeding seasons and the asynchrony among individuals during each breeding season. As we wanted to disentangle these two processes, we assessed a relative laying date for each breeding event, defined as the laying date of the individual minus the average laying date of the population on a given season (in days).

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Breeding success was defined as the proportion of chicks fledged depending on the number of eggs laid (two). Breeding events were considered second clutches if they were the second time an individual laid eggs within the same season, whether the first clutch was successful or not.

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### 2.2 Adult body conditions
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Adult body mass at the beginning of the breeding season was defined as the closest recorded mass from the laying date (APMS) entering the colony within five-days before the laying date. Adult body mass at the end of breeding was considered the closest recorded mass from chick fledging (APMS) of a parent leaving the colony for five days after fledging. Relative penguin mass change during breeding was considered as the quantity of mass gained or lost during the breeding event (mass at the end minus mass at laying) divided by the individual start mass (mass at laying) to account for variability in individual size. In many cases, mass at the beginning (70% of non-detection) and/or end (62% of non detection) of the breeding season was unknown due to lack of detection in this restrained period. However, we decided to favour the use of a mass representative of these two periods rather than expand the period of detection to increase the quantity of data available.

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## 2.3 *Chick growth and care*

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Chick growth quality was determined by the use of two common proxies: the mass at fledging (the last recorded mass in the colony, i.e. overall chick condition at independence) and the length of the guard period, as longer guard periods result in higher growth and fledging success due to longer intensive parental care (Chiaradia and Nisbet, 2006).

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# 3. Statistical analysis

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All analyses were performed using R 3.5.1 and RStudio 1.1.456. Data significance was accepted with an error threshold of 5%. Results are presented as means ± standard errors (SE). Whenever running a linear model (or linear mixed model, LMM), the normality of the residuals was tested using density plots and q-q plots. When more than one explanatory variable was included as a fixed effect in a model, the best model was selected according to Akaike's Information Criterion (AIC) backward model selection starting from full model unless otherwise specified. When the difference in AIC was lower than 2, the most
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parsimonious model (i.e. the one with the least variables) was retained (Burnham & Anderson 2004). Details about each model selection process can be found in Supplementary Material S1 to S10. The correlations among the different breeding variables of this study are also presented in *Supplementary Material S11*.

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### 3.1 Repeatability of penguin phenology and associated causes

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Repeatability describes the part of total phenotypic variance (i.e. sum of within-group and between-group variances) explained by between-group sources and is often used to quantify stable individual differences (Nakagawa and Schielzeth 2010). Here, we assessed the repeatability of the laying date across individuals using rptR 0.9.22 package (REP = *Laying Date* ~ (1 | *Individual*))). The potential effect of sex or age on repeatability was also assessed (REP = *Laying Date* ~ *Sex and/or Age* + (1 | *Individual*)), to account for the effect of processes such as gain of experience or senescence on breeding timing. Repeatability was considered to be significantly different from zero based on a 95% confidence interval.

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### 3.2 Effect of phenology on current and future breeding events

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We assessed the effect of individual laying date and relative laying date on breeding outputs using generalised linear mixed models from lme4 1.1-19 package. For binary and discrete interval variables, i.e. probability of second clutch and breeding success (from 0 to 2), binomial GLMMs were performed, while LMMs were performed for adult and chick growth conditions.

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#### *Effects of laying date on current breeding event: models at the pair level*

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Because little penguins exhibit bi-parental care, breeding success and chick growth condition (guard length and age/mass at fledging) were assessed per pair and models were run at the pair level with the breeding season and the two parents identities as a random intercepts as
well as the clutch number and laying date as fixed effects in interaction (hereafter symbolized by *). 207
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Pair breeding success, guard length or chicks mass at fledging ~ Laying date * Clutch + (1 | Season)+(1|MotherID)+(1|FatherID). 209
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Effects of laying date on subsequent breeding events (second clutch or next year performances): models at the individual level 211
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Because divorce rates are quite high in this species (Simpson et al. in review), the probability of performing a second clutch as well as the effects on the next breeding season was assessed at the individual rather than the pair scale and individual, pair ID age and breeding season were added as random variables while the effect of laying date was tested in interaction with sex, as males and females could display different reaction norms. 213
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Second clutch probability or next year performances ~ Laying date * Sex + (1 | Season) + (1|Individual) + (1|Age) + (1|Pair). 218
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When looking at the effect of the laying date on the next breeding season, only the first laying date (i.e. start of breeding period) was considered in the case of multiple clutches, as subsequent laying should depend on previous overall breeding timing rather than on previous second clutch. 220
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Effects of laying date on adult body condition: models at the individual level 224

Similarly, the effect of laying date and relative laying date on the adult condition (mass change during breeding) was assessed at the individual level with individual, pair ID, age and breeding season as random variables and the interaction of sex and clutch number (as adult condition is expected to be overall lower and effect of timing stronger in the second clutch). 225
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Mass change ~ Laying date * Sex * Clutch + (1 | Season) + (1 | Individual) + (1|Age) + (1|Pair).

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### 3.3 Link between current breeding conditions and next laying

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Effect of current breeding season conditions such as mass at the end of breeding, guard length, chick mass on the next laying date was also tested using LMM with sex interaction and random effect of the breeding season, age, pair as well as individual.

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Next year laying date ~ Previous breeding season conditions * Sex + (1 | Season) + (1|Individual) + (1|Age) + (1|Pair).

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Different models were used to test these parameters individually in order to avoid significant loss of data points due to missing chicks and adult mass information.

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In order to disentangle potential carry-over effects from individual quality (e.g. poor quality individuals presenting constantly poor breeding conditions and delayed phenology, inducing interannual correlations), the correlation between individual laying dates at different year lags (from 1 to 5 years) was tested. On top of this, we assessed the relation between individual relative laying dates (i.e. relative to yearly population average) and the annual shift between current and subsequent relative laying date using a linear mixed model including random effect of individual.

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Difference in relative laying date ~ Relative laying date + (1| Individual).

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This method aims at distinguishing a system mainly driven by individual quality in which shift in laying date should be limited and independent from previous season timing, from a system mainly driven by carry-over effects in which late breeders should display an increased recovery period (i.e longer time between two subsequent laying). As experience and senescence processes can have a major effect on the individual laying date shift, these
analysis as well as multiannual correlations were only conducted on individuals aged 5 to 16
year old, to avoid important age effects following Saraux & Chiaradia (2021).

To test for a potential recovery effect from skipping breeding, we once again used the
difference in relative laying date (RLD) between two subsequent breeding seasons. More
precisely, we looked for a potentially significant difference depending on previous breeding
status (i.e. between the individuals breeding for the second time in a row and those that
skipped the last breeding event) using a linear mixed model, including the random effect of
the breeding season and individual ID and age.

Difference in RLD ~ Previous breeding status + (1 | Season) + (1 | Individual) + (1 | Age).

## 261 Results

Penguins breeding seasons spanned from the end of July to mid-December (around 5 months,
*Figure 1*) with high variations across years, individuals breeding as early as June and as late
as February. Regarding intra-season variability, most individuals tended to breed in a two
month interval before and after the population average (*Figure 1*), although some breeding
events occurred more than 100 days before or after the population average (more than six
months between the very first and very last event).

## 268 1. Consistency in phenology at the individual level

We assessed the repeatability of individual laying dates across life using increasingly detailed
models to account for some other factors inducing variability in penguin phenology.
Individual identity explained about 9% of repeatability, suggesting that laying date was
somewhat repeatable (R = 0.094 ± 0.018 SE, N = 388, n = 2215, p < 0.001) when taking
nothing else into account. When accounting for the individual age as a random variable,
individual repeatability in laying date improved to 17% (R = 0.166 ± 0.021, p < 0.001).
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Further adding the effect of sex into the model did not affect repeatability (R = 0.167 ± 0.022, p < 0.001).

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## 2. Effect of breeding timing on current and next breeding seasons

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### a) Breeding timing effect on the current breeding season

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Effects of laying date were tested using both calendar and relative laying dates (i.e. laying date relative to the population average during the current season). This approach allowed for the examination of the two main components of laying variability among individuals: inter-annual differences and intra-seasonal asynchrony. As both analyses displayed very similar results and amplitude (i.e. predominant effect of intra-seasonal asynchrony on interannual variability), only the effects of raw laying dates are discussed below. More information on relative laying dates is available in the *Supplementary Material S12*.

Regarding breeding output, later breeding was associated with a substantial decrease in breeding success, even stronger during second clutches (binomial GLMM, n = 1517, N = 273, p < 0.001, *Figure 2 A and 3 A*). In terms of chick care, later breeding timing was linked to shorter guards (i.e. intensive chick care, -0.04 ± 0.00 days of guard per day of delay, LMM, n = 1201, N = 253, p < 0.001, effect of clutch not retained by model selection with ΔAIC < 2, most parsimonious model kept, *Figure 1 D and 2 B*). Penguins that bred later in the season also had chicks with lower fledging mass, during first clutches (-0.70 ± 0.20 g per day of delay, LMM, n = 715, N = 184, p < 0.001, *Figure 2 E and 3 B*, effect of clutch first retained by model selection with ΔAIC = 16), although the opposite trend was observed during second clutches (i.e. significant clutch interaction, p = 0.002, 0.41 ± 0.35 g per day of delay, n = 171 second clutches).
Delayed breeding also had significant effects on the adult condition during the season. 299
Penguins that laid eggs later in the season experienced more significant mass loss during 300
breeding, with effect of clutch (ΔAIC < 2) or interaction of sex (ΔAIC = 4) not retained by 301
model selection, (-0.07% ± 0.02% mass at the end of the season per day of delay, LMM, n = 302
561, N = 203, p = 0.001, different intercept per sex, p = 0.020, Figure 2 C). Late-breeding 303
adults were way less susceptible to attempt second clutches (-5.1% probability to do a second 304
clutch per day of delay, GLMM, n = 2152, N = 462, p < 0.001, interaction and effect of sex 305
not retained by model selection (ΔAIC = 4 and 2 respectively), Figure 2 B and 3 A). 306

b) *Delayed effect of breeding timing on future seasons* 307

Delayed breeding not only impacted current season performance but was also linked to lower 308
breeding success in the following season (Figure 4). Later laying was associated with reduced 309
probability of breeding in the following season (excluding dead penguins, -0.4% ± 0.2% 310
probability to breed the following year per day of delay, GLMM, n = 1890, N = 415, p = 0.05, 311
interaction and effect of sex not retained by model selection, ΔAIC = 4 and < 2 respectively, 312
*Figure 4 A and 3 C*). When penguins still bred on the following season, their breeding success 313
was lower (-0.4% ± 0.1%, GLMM, n = 1568, N = 345, p = 0.005, interaction and effect of sex 314
not retained by model selection, ΔAIC = 3 and < 2 respectively, *Figure 4 C and 3 C*), and 315
they had much less probability to attempt a second clutch (-1.0% probability per day of delay, 316
GLMM, n = 1568, N = 345, p < 0.001, interaction and effect of sex not retained by model 317
selection, ΔAIC = 4 and 2 respectively, *Figure 4 B and 3C*). The relative laying date affected 318
the next breeding season to the same extent as the calendar laying date (see *Supplementary* 319
*Material S13* for more details). 320

**3. Cycling effect of the previous breeding season on phenology** 321

Penguins that bred late in the previous season were more likely to breed later again, as the 322
timing of their previous breeding was strongly correlated with their current breeding timing 323
(Pearson's correlation = 0.91). On average, each day of delay in the previous season was associated with a 0.14 ± 0.02-day delay in the current season (LMM, n = 1568, N = 345, p < 0.001, interaction and effect of sex not retained by model selection, ΔAIC = 4 and < 2 respectively, Figure 5 A). Regarding the carry-over effect of chick care (i.e. increased parental investment), penguins were more likely to breed late when they had longest guard periods the previous season (0.44 ± 0.15 day later per day of guard, LMM, n = 1269, N = 311, p = 0.002, Figure 5 B, effect and interaction of sex not retained by model selection with ΔAIC = 3 and < 2 respectively) and when they fledged lighter chicks (although relation insignificant, 0.01 ± 0.01 day later per gram, LMM, n = 759, N = 257, p = 0.091, Figure 5 C, effect and interaction of sex not retained by model selection with ΔAIC = 3 and < 2 respectively). The effect of overall body condition at the end of previous breeding season on penguin laying date was not tested here because null model was favorised by model selection (ΔAIC < 2, most parsimonious model kept)

Regarding interannual correlations in laying date, we found a significant relationship between individual relative laying date at year t and t+1 (Pearson's correlation test = 0.15 ± 0.05). However this relation became insignificant for all higher lags (from t+2 to t+5), indicating the overall weak correlation of individual laying across life. On the opposite, the individual recovery time between consecutive laying was importantly related to the previous relative laying date (LMM, 0.9±0.0 day longer recovery between two consecutive laying per day of delay in laying, R² = 0.43, p < 0.001, n = 1296, N = 286, Figure 6).

Finally, the potential effect of skipping a breeding event, only 111 of the 1629 non-first breeding events followed a skipped event (6.8%, 80 unique individuals), making it a rare occurrence in our model. Among these rare events, individuals that missed previous breeding did not breed earlier than others (LMM, p = 0.65, n = 1740, N = 421) and did not advance their relative breeding timing (i.e. number of days gained compared to the previous season)
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during the next event more than the ones that did not skip (LMM, p = 0.91, n = 1378, N =
319).

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Discussion
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Through an extensive study of over 2500 breeding events from more than 500 individuals over 20 years, we provide new insights into the impact of delayed breeding phenology at the individual level using little penguins as a model. Our research highlights the critical trade-off between maximizing immediate breeding outputs and saving energy for later breeding events, a key factor of breeding decisions for long-lived species (Stearns 1989). We reveal how the timing of breeding not only influences current reproductive success but also has significant carry-over effects, shaping future breeding seasons. Our work underscores the importance of breeding cycle timing in individual life-history strategies, offering valuable implications for understanding reproductive dynamics in long-lived species.

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The importance of individual breeding timing on reproductive outputs is well documented in seabirds, including lower breeding success (Reed et al. 2009, Ramírez et al. 2016) or clutch size (Moe et al. 2009). The link between late phenology and consecutive deteriorated breeding could be the result of a mismatch with the available resources during chick-rearing (Hipfner 2008, Shultz et al. 2009), inducing an increased foraging effort (Regular et al. 2014). However, the path through which current and future success are affected by low resource availability (i.e. poor chick development and parents' exhaustion; Regular et al. 2014) are very often assumed and rarely tested due to the difficulty of gathering this type of data. We tested the effect of inter-individual variability in breeding phenology on breeding output and on breeder body condition and offspring development.

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We confirmed that later breeding was associated with a significant decrease in subsequent
breeding success (Regular et al. 2014, Ramírez et al. 2016), which was even more visible for
the second breeding attempt within a season. Even when breeding was successful, we
highlighted that late breeding led to lighter chicks at fledging, although unrelated to younger age. This suggests that late breeding is probably associated with fewer resources available in the environment during chick-rearing (Hipfner 2008, Shultz et al. 2009), which was already shown to affect little penguins' breeding success (Joly et al. 2022). While little penguins' breeding success and even lifetime fitness (Joly et al. 2023) depend for an important part on individual capacity to fledge chicks, these results suggest that breeding timing effects on fitness could be even stronger when taking into account chick survival after fledging as chick mass at fledging is expected to affect birds' post-fledging survival (Coulson and Porter 1985, Krementz et al. 1989, Magrath 1991).

While we showed an immediate effect of late breeding on chick body condition at fledging, long-lived species are expected to be able to easily buffer a poor breeding event at the lifetime scale by allocating more energy to their future breedings (Stearns 1989). Here, we found that late breeding not only affected chick growth but also affected the parent body condition throughout the breeding season (i.e higher mass loss during breeding). Late breeding is thus more likely to result in overall adult deteriorated body condition while breeding, probably through a decreased food availability (Monaghan 2007, Koyama et al. 2021). This deterioration may trigger a reduced investment in the chicks (Martins and Wright 1993, Saraux et al. 2011), including complete nest abandonment (Groscolas et al. 2008, Spée et al. 2010), to favour breeder survival (Williams 1966, Stearns 1992), which is likely to partly explain the low breeding success of late breeders.

While late breeding is often associated with unfavourable outcomes, it remains unclear why some birds continue to breed late. One plausible hypothesis is that reduced body condition at the end of the breeding season prolongs post-breeding recovery time, leading to significant carry-over effects on subsequent breeding. (Fayet et al. 2016). Indeed, birds facing strong carry-over effects are expected to adjust their breeding timing in the following season to
increase pre-breeding energy intake (Hennin et al. 2016, Gatt et al. 2021). Evidence of a multiannual relation between individual phenology and breeding output could be the mark of a cycling effect where breeding conditions affect subsequent breeding timing, affecting following breeding conditions, but could also simply be the marker of differences in individual quality. In our case however, carry-over effects seemed to be the major process driving multiannual effect of phenology, as we established a clear relation between individuals' delay between two subsequent breeding seasons and their breeding timing during previous season. This suggests that individuals facing poorer conditions (i.e. late breeders) may need an increased recovery period before attempting a new breeding season, leading to further delay in their breeding timing and to overall poorer breeding conditions.

We found a clear link between late breeding on one breeding season and subsequent breeding season, including lower breeding success (Shoji et al. 2015) and significantly lower probability of attempting a breeding event (first or second). While inter-individual variability in breeding timing was already known to affect direct breeding outputs (Reed et al. 2009), these results suggest that its effect on the lifetime scale might be even more critical through an interannual impact on fitness. Furthermore, we highlighted that delayed laying date tended to induce later timing for the next breeding event, confirming this multi-annual effect (Fayet et al. 2016). In our case, delayed laying was associated with overall poorest conditions on previous breeding season, including chick investment. This could confirm the hypothesis that seabirds need to reach a certain body condition threshold to start breeding (Chastel et al. 1995b, Robinson et al. 2005, Sorensen et al. 2009), and that this recovery threshold is harder and longer to reach when conditions faced during previous breeding event were overall more exhausting. Although little penguins are expected to be mainly income breeders, this study (as well as others, Salton et al. 2015) shows that the capital breeding dimension should not be neglected, as often shown in migrating birds (Graña Grilli et al. 2018, Steenweg et al. 2022).
With those results, we seem to highlight carry-over effects as a significant driver of the variability in seabirds' phenology (Shoji et al. 2015, Fayet et al. 2016) at the inter-individual scale. However, such carry-over effects would be expected to be broken by skipping a breeding season, which did not seem to be happening in our case. Indeed, we found no effect of a skipped breeding event on subsequent breeding timing (including no significant advance of relative breeding timing) or the capacity to counterbalance carry-over effects, which was a sporadic event. This suggests that these observed carry-over effects might greatly depend on individual quality; poor-quality individuals facing carry-over effects while good-quality individuals manage to cope with the cost of reproduction. This is consistent with previous studies arguing that skipped breeding events are more the reflection of poor individual quality (Cam et al. 1998) than a valuable strategy to cope with carry-over effects (Reed et al. 2015).

Indeed, while conditions faced during previous breeding events are a major driver of inter-individual differences in success and fitness (Harrison et al. 2011, O'Connor et al. 2014), the difference in penguins' phenology may also be the result of the fixed heterogeneity arising from intrinsic individual differences (Cam et al. 2016). These intrinsic differences can result in important variations in individual quality, leading to differences in performances through life (Lescroël et al. 2009). Here, we found that many individuals tended to breed earlier than others even if they produced larger chicks in previous years (indicating higher investment). This suggests that some individuals may perform well while experiencing minimal carry-over effects, likely due to their intrinsic high quality (Joly et al. 2023).

A key method for assessing consistency in (i.e. intrinsic differences) individual behavioural traits is to measure the trait repeatability (Bell et al. 2009, Carlson and Tetzlaff 2020). Our study highlights that around 17% of the variation in individual laying date was repeatable, which is consistent with previous studies on other seabird species (Sydeman and Eddy 1995, Fayet et al. 2016, Dobson et al. 2017). The consistent inter-individual differences, likely due
449

to genetic factors (Dochtermann et al. 2019) or early-life conditions (Lindström 1999, Lee et al. 2012) may account for a significant portion of the variability in laying dates, including their initial breeding experiences.

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## Acknowledgements

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We thank Phillip Island Nature Parks for their continued support and commitment to penguin research. We also sincerely thank Paula Wasiak, Leanne Renwick, Marg Healy, Alona Charuvi, Marjolein van Polaten Petel, Ross Holmberg, and several past students and volunteers for their tireless support in collecting these data. Without them, this work would not be possible. We also thank the two reviewers of this manuscript for their contribution.

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## Declarations

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**Funding:** The long-term dataset received several funding sources over the years: the Penguin Foundation, Australian Academy of Science, Australian Research Council, Australian Antarctic Division, Kean Electronics and ATT Kings. This research project was funded by the Agence National de la Recherche APEX project (ANR-21-CE02-0007).

464

**Conflicts of interest:** We declare no conflicts of interest.

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**Ethics approval:** The study was conducted with research permits issued by the Department of Environment, Land, Water and Planning, Victorian State Government, Australia, and ethics approvals from the Animal Ethics Committee of Phillip Island Nature Parks.

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**Consent to participate/for publication:** Not applicable.

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470

**Availability of data:** Data will be made available on a public repository such as Dryad upon acceptance of the manuscript.

471

472
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646

647
649 **Figure 1:** Annual repartition of laying date in Little penguins' population from 2000 to 2020.

650 **Figure 2:** Breeding parameters of little penguins based on their laying date with linear mixed
651 model or generalised additive model (red curve) ± SE (grey area). Blue curve (A, E)
652 represents second clutches, and orange/lightblue curves (C) represents differences between
653 sexes. Number of points as well as p-values (for first and second clutches when relevant) are
654 presented.

655 **Figure 3:** Breeding effects on little penguin breeding (i.e. breeding success and second clutch, A), mass loss (B) and chick caring (i.e. guard length and weight of chicks at fledging, B) and breeding next season (i.e. probability of breeding, probability of second clutch and breeding success, C) including ratio (i.e. for breeding (binomial GLMM) and estimates of scaled variables for others (GLMM) and CI95%).
656
657
658
659

660 **Figure 4:** Breeding probability (first and second clutch) and breeding success of little penguins during next season based on their laying date on current season with linear mixed model (red curve) ± SE (grey area).

663 **Figure 5:** Laying date of little penguins based on previous season laying date, guard length and average mass of chick fledging with linear mixed model (red curve) ± SE (grey area).

665 **Figure 6:** Difference in relative laying date between two subsequent seasons depending on previous relative laying date with linear mixed model (red curve) ± SE (grey area).
<figure><img src="image_2.png" /><figcaption>Figure 1</figcaption></figure>
<figure><img src="image_3.png" /></figure>

A

n = 1517, all p < 0.001

<figure><img src="image_4.png" /></figure>

B

n = 2152, p < 0.001

<figure><img src="image_5.png" /></figure>

C

n = 561, p = 0.001

<figure><img src="image_6.png" /></figure>

D

n = 1201, p < 0.001

<figure><img src="image_7.png" /></figure>

E

n = 715, p < 0.001 and p < 0.01

Laying date (day)
<figure><img src="image_8.png" /><figcaption>Figure 3</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Figure 4</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>Figure 5</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>Figure 6</figcaption></figure>