# Slow life-history strategies are associated with negligible actuarial senescence in western Palaearctic salamanders

Hugo Cayuela, Kurtuluş Olgun, Claudio Angelini, Nazan Üzüm, Olivier Peyronel, Claude Miaud, Aziz Avci, Jean-François Lemaître, Benedikt R

Schmidt

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## ► To cite this version:

Hugo Cayuela, Kurtuluş Olgun, Claudio Angelini, Nazan Üzüm, Olivier Peyronel, et al.. Slow life-history strategies are associated with negligible actuarial senescence in western Palaearctic salamanders. Proceedings of the Royal Society B: Biological Sciences, 2019, 286 (1909), pp.20191498. 10.1098/rspb.2019.1498. hal-02390014

HAL Id: hal-02390014

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Submitted on 16 Jun 2025

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1 Slow life-history strategies are associated with negligible actuarial senescence in Western Palearctic salamanders

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4 Hugo Cayuela¹, Kurtuluş Olgun², Claudio Angelini³, Nazan Üzüm², Olivier Peyronel⁴, Claude

5 Miaud⁵, Aziz Avci², Jean-François Lemaitre⁶, Benedikt R. Schmidt⁷,⁸

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7 ¹Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC G1V 0A6,

8 Canada

9 ²Department of Biology, Faculty of Arts and Sciences, Adnan Menderes University, Aydin, Turkey

10 ³Via G. Marconi 30, 04018 Sezze, Italy

11 ⁴Syndicat de gestion des gorges de l'Ardèche, 07700 Saint-Remèze

12 ⁵PSL Research University, CEFE UMR 5175, CNRS, Université de Montpellier, Université Paul-

13 Valéry Montpellier, EPHE, Biogéographie et Ecologie des vertébrés, Montpellier, France

14 ⁶Univ Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Évolutive UMR 5558,

15 F-69622, Villeurbanne, France

16 ⁷Institut für Evolutionsbiologie und Umweltwissenschaften, Universität Zürich,

17 Winterthurerstrasse 190, 8057 Zürich, Switzerland

18 ⁸Info fauna karch, UniMail, Bâtiment G, Bellevaux 51, 2000 Neuchâtel, Switzerland

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20 Corresponding author: Hugo Cayuela

21 Email: hugo.cayuela51@gmail.com

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23 Word count: 7259

24 Number of tables: 0

25 Number of figures: 3

26 Supplements: 1

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28 **Abstract**

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30 Actuarial senescence has been viewed for a long time as an inevitable and uniform process.
31 However, the work on senescence has mainly focused on endotherms with deterministic growth
32 and low regeneration capacity during the adult stage, leading to a strong taxonomic bias in the study
33 of aging. Recent studies have highlighted that senescence could indeed display highly variable
34 trajectories that correlate with species life history traits. Slow life histories and indeterminate
35 growth seem to be associated with weak and late senescence. Furthermore, high regenerative
36 abilities could lead to negligible senescence in ectotherms. However, demographic data for species
37 that would allow testing of these hypotheses are scarce. Here, we investigated senescence patterns
38 in "true salamanders" from the Western Palearctic. Our results showed that salamanders have slow
39 life histories and that they experience negligible senescence. This pattern was consistent at both
40 intra- and interspecific levels, suggesting that the absence of senescence may be a phylogenetically
41 conserved trait. The regenerative capacities of salamanders, in combination with other
42 physiological and developmental features such as an indeterminate growth and a low metabolic
43 rate, likely explain why these small ectotherms have lifespans similar to that of large endotherms
44 and, in contrast to most amniotes, undergo negligible senescence. Our study seriously challenges
45 the idea that senescence is a ubiquitous phenomenon in the tree of life.

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47 **Key words:** aging, actuarial senescence, life history, urodeles, salamanders

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50 **Introduction**

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52 The great diversity of life histories continues to fascinate population biologists (Stearns 1976, 53 Dammhahn et al. 2018, Wright et al. 2019). There have been many attempts to summarize the 54 variety of life history patterns that are observed (e.g., Pianka 1970, Sæther 1988, Bielby et al. 2007).

55 Among the spate of life history traits, senescence is generally defined as a physiologically-caused, 56 irreversible increase in mortality (i.e., actuarial senescence; hereafter senescence) and/or a decline 57 in fertility with age (i.e., reproductive senescence) (Hamilton 1966, Rose 1991). Historically, 58 senescence was expected to show a limited amount of variation across species. The senescence 59 process was expected to be ubiquitous among age-structured populations (Hamilton 1966), which 60 led to the view that senescence was an unavoidable process in organisms with a clear distinction 61 between somatic and germ lines (Kirkwood 1977, Ackermann et al. 2003, Nussey et al. 2013). In 62 addition, regardless of the species considered, the age at the onset of senescence was expected to 63 be immutably set at the age of first reproduction (Williams 1957, Hamilton 1966). This long-held 64 view was overturned when it was shown that there is a bewildering diversity of senescence 65 patterns across animal and plant species (Jones et al. 2014, Baudisch et al. 2013, Gaillard & 66 Lemaître 2017, Colchero et al. 2019). There is an obvious need to further describe and explain the 67 diversity of senescence patterns which was recently reinforced by the observation that senescence 68 patterns can strongly affect population growth rates and how species respond to environmental 69 change (Colchero et al. 2019).

70 In a recent analysis of senescence on a wide range of taxa Jones et al. (2014) demonstrated 71 patterns of senescence are more diverse than previously thought. Although Jones et al. (2014), and 72 more recently Colchero et al. (2019), present results from a broad variety of species, their studies 73 highlighted the lack of data for many taxa and thus there is still a great need to uncover and explain 74 senescence patterns. In particular, it is necessary to evaluate the extent to which species can escape 75 senescence or even show ‘negative senescence’ and to determinate the eco-evolutionary roots of 76 such patterns (Finch 1998, Vaupel et al. 2004, Jones & Vaupel 2017). As the life history theory of 77 aging postulates that senescence is related to somatic maintenance (Lemaître et al. 2015, Kirkwood 78 2017), one may expect that species who invest more into this item of expenditure such as “slow” 79 species (i.e., low annual fecundity and high adult survival); should show slower rates of senescence 80 (e.g. Ma & Gladyshev 2017). This expectation is supported by the findings of Jones et al. (2008) 81 who showed that in both mammals and birds, the onset and rate of senescence are predicted by 82 generation time and age at maturity. Since the life histories of species can be arranged along a fast- 83 slow life history continuum (Stearns 1983, Harvey & Zammuto 1985, Promislow & Harvey 1990,
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Bielby et al. 2007), the speed of the life history can be used to predict senescence (Jones et al. 2008). Later, Jones et al. (2014) showed that the initial explanation of Jones et al. (2008) did not fully account for the diversity of senescence patterns, suggesting that other mechanisms may be at work as well. For example, their study revealed the absence of senescence in *Hydra* (and few other organisms), potentially allowed by regenerative capacity (Martinez 1998).

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Most of our understanding of senescence in wild animal populations is based on mammals and birds because there are many long-term individual-based data sets for these species (Jones et al. 2014). Yet, patterns of senescence among mammals is rather uniform. For example, Colchero et al. (2019) found that bathtub-shaped mortality trajectories were most commonly observed in ungulates and carnivores. The data set of Colchero et al. (2019) included only four amphibian species but four different models explained the data best (simple logistic, bathtub logistic, Gompertz, Weibull), suggesting great interspecific diversity within the amphibians. Interestingly, senescence was negligible in a salamander (*Salamandra salamandra*), an organism with an indeterminate (i.e., continuous) growth (Bouzid et al. 2017) that is well known for its regenerative capacity at the adult stage (Yokoyama 2008, Poss 2010, Seifert & Voss 2013).

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Here, we investigated how slow life histories with an implicit high level of investment in somatic maintenance are associated with a negligible actuarial senescence in a clade of salamanders from the Western Palearctic (known as the “true salamanders”). We used both unpublished and published capture-recapture data for our analyses. First, we analyzed novel demographic data from a poorly known Mediterranean salamander (*Lyciasalamandra fazilae*) and examined if this species had a slow life history (i.e., high adult survival and low recruitment) consistent with the other species of true salamanders (Warburg 2007, Sinsch et al. 2017). Then, we examined senescence patterns in *L. fazilae* and two other species, *Salamandrina perspicillata* and *Salamandra salamandra*, from Western Europe. We expected negligible senescence in the three taxa and hypothesized that this pattern was consistent among populations.

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## Material and methods

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### Demography of *Lyciasalamandra fazilae*

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### Study species and capture-recapture survey

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*L. fazilae* is terrestrial salamander occurring along the southern Anatolian coast in Turkey. This species is a member of the phylogenetic clade called “true” salamanders that encompasses the

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genera *Salamandra*, *Lyciasalamandra*, *Mertensiella*, *Salamandrina*, and *Chioglossa* (Weisrock et al. 2006). *L. fazilae* is viviparous salamander that gives birth to one or two fully metamorphosed young after one year of gestation. Sexual maturity is attained at an age of three years in both sexes (Olgun et al. 2001). The individual growth curve presents an asymptotic trend even if adult salamanders seem to continue to grow over their entire lifespan (Olgun et al. 2001).

The study was conducted on a population of *L. fazilae* between 1999 and 2009 in western Turkey near Dalyan (N 36° 50', E 28° 41'). A detailed description of the study area can be found in Olgun et al. (2001). Several capture-recapture sessions (in February, March, and April) were carried out each year. The salamanders were captured by hand, and were then released back in the place where they were initially caught after being marked using pit-tags, identified, and measured. The sex of the individuals was assessed using secondary sexual characters (Olgun et al. 2001). Juveniles were not included in the analysis because only 12 juveniles were encountered during the study but never recaptured. Furthermore, due to small size of the dataset (133 individuals marked), we pooled the two sexes in analyses to avoid model overparameterization. We assumed that sex should have a little influence on adult survival as males and females have the same age structure in the population (Olgun et al. 2001).

Body size of salamanders was determined by measuring snout-vent-length (SVL): individuals were measured from the tip of the snout to the posterior margin of the vent. We used the size data in multievent capture-recapture models to estimate size-dependent survival. We also benefited from age data assessed using skeletochronological analyses (a robust approach to evaluate age in amphibians, Sinsch 2015) for individuals marked over the period 1999-2003 (Olgun et al. 2001). Those age data were included in BaSTA models (Colchero & Clark 2012, Colchero et al. 2012) to examine age-dependent survival and mortality rate.

## 141 Multievent model with size-dependent adult survival

We quantified size-dependent annual survival using multievent capture-recapture models (Pradel 2005). Note that we did not perform goodness-of-fit tests before building the models since no test is currently available for multievent models; note that it was also possible to consider potential transience, trap-dependence, and recapture heterogeneity in BaSTA models presented below. We considered a model based on three latent states that include information about individuals' size. The states *s* and *l* correspond to small (SVL, from 45 to 60 mm) and large (SVL, from 61 to 81 mm) adults respectively; the classes were fixed to obtain a relatively similar number of observations in the two classes. The state *d* corresponds to the *dead* state. The models include three observations
coded as following in the capture histories: individuals that are not captured are coded ‘0’; small and large individuals captured are coded ‘1’ and ‘2’ respectively.

At their first capture individuals may occupy two distinct states of departure, s and l. At each time step, the information about individual state is progressively updated through two successive modeling steps: (1) survival, and (2) size transition. Each step is conditional on all previous steps. At the first modeling step, survival information is updated. A small individual may survive with a probability $\varphi_s$ or die with a probability $1-\varphi_s$. A large individual can survive with a probability $\varphi_l$ or not with a probability $1-\varphi_l$. These results in the following matrix (the state of the individual at t-1 is in column and state at t is in row):

$$ \begin{bmatrix} \varphi_s & 0 & 1-\varphi_s \\ 0 & \varphi_l & 1-\varphi_l \\ 0 & 0 & 1 \end{bmatrix} $$

In the second modeling step, information about individual size is updated. A small individual can become a large individual with a probability $\delta_s$ or remain in the same class with a probability $1-\delta_s$, leading to the following matrix:

$$ \begin{bmatrix} 1-\delta_s & \delta_s & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{bmatrix} $$

The last component of the model links observation to states. Small and large individual can be captured with a probability $p_s$ or $p_l$, which results in the following matrix:

$$ \begin{bmatrix} 1-p_s & p_s & 0 \\ 1-p_l & 0 & p_l \\ 1 & 0 & 0 \end{bmatrix} $$

This parameterization was implemented in the program E-SURGE (Choquet et al. 2009). We ranked models using AICc and Akaike weights (w). If the Akaike weight of the best supported model was less than 0.9, we used model-averaging to obtain parameter estimates. We examined our hypotheses about survival and recapture probability from the following general model [$\varphi$(size), $\delta$(.), $p$(t + size)]. The effects considered in the models were size and year (t). We hypothesized that: survival $\varphi$ probability differed between the two size classes (i.e. small and large). We also expected that recapture probability varies according to size and year. Age transition was set constant (.) in the model. We tested all the possible combinations of effects, resulting in the consideration of eight competing models (Supplementary material, Table S2).

Multievent model for recruitment
We estimated recruitment rate of small-size adult using a modified Pradel (1996) model in which
recruitment is modeled by reversing capture histories and analyzing them backwards. Recruitment
probability was estimated as the probability that a small-sized individual present at *t* was not present
at *t*−1, i.e. the proportion of “new” small individuals in the population at *t*. The model had the
structure similar to that of survival model. The survival matrix was replaced by the recruitment
matrix. At each time step, small individuals may be recruited with a probability $\psi_s$ or not with a
probability $1 - \psi_s$, leading to the following matrix:

$$ \begin{bmatrix} 1 - \psi_s & 0 & \psi_s \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{bmatrix} $$

The size transition matrix was also modified to allow reversed size transition:

$$ \begin{bmatrix} 1 & 0 & 0 \\ \delta_L & 1 - \delta_L & 0 \\ 0 & 0 & 1 \end{bmatrix} $$

This parameterization was implemented in E-SURGE program. We considered the most
general model [$\psi(.)$, $\delta(.)$, $p(t + size)$]. We examined all the possible combination of effects leading
to the consideration of four candidate models.

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195 *Age-dependent survival and senescence patterns in true salamanders*

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197 Capture-recapture data

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199 To estimate age-dependent survival and senescence, we re-analysed two data sets of true salamanders that were analysed previously. The capture-recapture data of *S. perspicillata* was collected over a 9-year period (1998-2006) in a population of central Italy (Monti Lepini, Latium; Angelini et al. 2010). The capture-recapture data of *S. salamandra* were collected in two populations from southern France (Ardèche region, pop1) and northwestern Germany (Nordrhein-Westfalen, pop2). pop1 and pop2 were surveyed over 8-years (2008-2015) and 21-years (1965-1985) period, respectively (Cayuela et al. 2017, Schmidt et al. 2005). A summary of the age-dependent capture-recapture data in the four populations of salamanders is provided in Supplementary material, Table S1. In all cases, the survey length was equal or longer than the mean lifespan of adults in the four populations (Supplementary material, Table S1). Given the simulations of Colchero & Clark (2012), we are therefore confident in our ability to detect senescence if it actually occurred. Note that the sex was not considered in the further analyses as only females were caught in *S. perspicillata* (males do not occur at breeding sites) and because sex cannot be easily ascertained by non-expert observers in *S. salamandra*.
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## Results

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## Age-dependent survival and mortality rate

We investigated actuarial senescence patterns in the three salamander species using Bayesian survival trajectory analyses implemented in the R package BaSTA (Colchero & Clark 2012, Colchero et al. 2012). BaSTA allowed us to account for imperfect detection, left-truncated (i.e., unknown birth date) and right-censored (i.e., unknown death date) capture-recapture data in our analysis. It allows estimating two demographic functions: cumulative probability survival until a given age and mortality rate (i.e., hazard rate) at a given age. Given the results of previous analyses (Schmidt et al. 2005, Angelini et al. 2010, Cayuela et al. 2017), we allowed recapture probabilities to vary among years. As the study period and number of survey years differ among populations (Supplementary material, Table S1), the four populations and species were analyzed separately. We used DIC to select models that fit the data best and we compared the outputs of the best-supported model of the four populations by inspecting mean estimates and 95% CI. This allowed us to investigate population/species-specific variation in the shape of the age-specific mortality patterns. We considered the four mortality functions implemented in BaSTA: exponential, Gompertz, Weibull and logistic. For the three last functions, we considered three potential shapes: *simple* that only uses the basic functions described above; *Makeham* (Pletcher 1999); and *bathtub* (Siler 1979). As individuals cannot be individually surveyed before their sexual maturity (three years old in the three species), we conditioned the analyses at a minimum age of three. Four MCMC chains were run with 50000 iterations and a burn-in of 5000. Chains were thinned by a factor of 50. Model convergence was evaluated using the diagnostic analyses implemented in BaSTA, which calculate the potential scale reduction for each parameter to assess convergence. For all populations, we used DIC to compare the predictive power of each mortality function and its refinements (Spiegelhalter et al. 2002, Colchero et al. 2012b).

## Demography of *Lyciasalamandra fazilae*

Over the 8-year study period, we made 179 captures of salamanders. We identified 121 adults (51 males and 70 females) and 12 juveniles. The mean age was 5.5 years and the maximum was 10 years.
The best-supported survival model was [φ(.), δ(.), p(t + size)] (Supplementary material, Table S2); its Akaike weight was 0.54 and we therefore model-averaged the estimates. The recapture probability of small individuals was higher than that of large individuals and varied over time. In 2001, the recapture probability of small individuals was 0.05±0.05 while it was 0.01±0.01 in large individuals; in 2007, recapture probability of small and large individuals was 0.78±0.18 and 0.41±0.17 respectively. The probability that a small individual change of size class and became a large individual was 0.28±0.09. Annual survival did not differ between small (0.72±0.06) and large (0.75±0.04) individuals (Fig.2A).

The best-supported recruitment model was [ψ(.), δ(.), p(t + size)] (Supplementary material, Table S2); its AICc weight was 0.54 and we therefore model-averaged the estimates. The recapture probabilities were relatively similar to that provided by survival model; we did not report them for this reason. The rate of small individual recruitment was 0.15±0.15.

## Age-dependent survival and senescence in true salamanders

In *L. fazilae*, the age-specific capture-recapture data were best described by an exponential function (Supplementary material, Table S3). The probability of surviving was 0.75 until age four, 0.50 until age five, and 0.25 until age seven (Fig.2A). Furthermore, the model indicates the absence of age-dependent mortality rate: mortality rate remained stable (around 0.34) regardless of age (Fig.3A).

In *S. perspicillata*, the best-supported model included a Gompertz function (Supplementary material, Table S3). The probability of surviving was 0.75 until age five, 0.50 until age eight, and 0.25 until age 12 (Fig.2B). Moreover, our results indicate that age had no influence on mortality rate (Fig.3B). Mortality rate remained stable (around 0.20) regardless of age.

In *S. salamandra*, the best-supported model included a Weibull function in *pop1* and a Gompertz function in *pop2* (Supplementary material, Table S3). The probability of surviving was 0.75 until age five, 0.50 until age eight, and 0.25 until age 13 in *pop2* (Fig.2C); in *pop1*, the survival estimates were very imprecise (Fig.2D). Moreover, our results indicate that mortality rate was not affected by age (Fig.3C and 3D). Mortality rate remained stable (around 0.05 and 0.15 in *pop1* and *pop2* respectively) regardless of age.

## Discussion

The three species of true salamanders analysed in this study are characterized by a slow life history strategy (i.e., low recruitment and high adult survival). Survival of all three species of salamanders
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decreased slowly with age and mortality rate remained constant regardless of salamander age,
suggesting negligible actuarial senescence in this clade.

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*Demography of Lyciasalamandra fazilae*

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Using capture-recapture data we have provided the first detailed demographic characterization of *L. fazilae* and demonstrated that it is a species with a relatively "slow" life history. The survival estimate of our multievent model (mean annual adult survival = 0.74±0.05) was very close to the survival estimate (0.79) provided by the skeletochronological analysis in the same population (Olgun et al. 2001). We are therefore confident that the survival estimate of *L. fazilae* is not biased by a methodological artefact; for example, permanent emigration leads to underestimated survival rates (i.e., apparent survival) in capture-recapture studies (Schmidt et al. 2007). Our study revealed that the probability of surviving was 0.50 until age five, and less than 0.05 until age 12. These results are also congruent with skeletochronological data that reported a maximum longevity of 10 years in the population. Furthermore, we did not find evidence of an effect of body size on adult survival. It is possible that a small body size negatively affects survival at juvenile stage (as commonly reported in amphibians; e.g., Schmidt et al. 2012, Cayuela et al. 2016) and that the effect of size on survival vanishes at either some point before or rapidly after sexual maturation. Furthermore, our study also revealed that recruitment was relatively low in *L. fazilae* (0.15). This is likely due to the low fecundity of females that produce one or two young after a gestation of one year (Olgun et al. 2001). All together, these results indicate that *L. fazilae* has a relatively slow life history.

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*Slow life histories in true salamanders*

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Our study and previous ones (Schmidt et al. 2005, Angelini et al. 2010, Cayuela et al. 2017) indicate that true salamanders have slow life history strategies. First, adult survival is relatively high in this clade (Fig.1C). In *S. salamandra*, survival probability was 0.85 in both populations while it ranges from 0.86 to 0.90 among *S. perspicillata* populations, indicating little variation at the intraspecific level (Fig.1C). At the interspecific scale, survival is relatively high in these three genera, which suggests that a long lifespan is a highly conserved trait in salamanders of Western Palearctic. Yet, *L. fazilae* has a lower survival (0.74 and 0.79 from capture-recapture and skeletochronological analyses, respectively) than *S. salamandra* and *S. perspicillata* (Fig.1C). This pattern was also perceptible in the survival estimates provided by our study: a survival probability of 0.50 was

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reached at 5 years in *L. fazilae*, 7.5 years in *S. perspicillata*, and 8 years in *S. Salamandra* (in pop2,
the estimate of pop1 was very imprecise). These adult survival rates for true salamanders are higher
than for most anurans (Muths et al. 2017) and many newts and plethodontid salamanders (Jehle et
al. 1995, Bendik 2017, Cayuela et al. 2019) supporting the idea that these species exhibit slow life
histories.

Through a trade-off, the relatively long lifespan of salamanders is also associated with a
low annual fecundity (compared to other amphibians; Wells 2010, Oliveira et al. 2017) that is
modulated by their reproductive modes. Oviparous species have the highest annual fecundity (e.g.,
*Salamandra infraimmaculata*, 218 eggs per female per year, Sharon et al. 1997; *S. perspicillata*,
40-65 eggs, Angelini 2006, Rovelli et al. 2015). Salamanders with lecithotrophic viviparity (i.e.,
giving birth to larvae) have an intermediate annual fecundity (e.g., *S. salamandra*, 23 larvae per
female per year, Kopp & Baur 2000; *Salamandra algira*, 13 larvae, Reinhard et al. 2015) whereas
species with matrotrophic viviparity (i.e., giving birth to fully developed young) have the lowest
annual fecundity (e.g., *L. fazilae* and *Salamandra atra*, 1 young per female per year; Greven &
Thiesmeier 1994, Luiselli et al. 2001). Fecundity adjustments of true salamander result from
potentially rapid (less than 1000 generations, Velo-Antón et al. 2012) changes in reproductive
modes that may occur at the intraspecific level (Velo-Antón et al. 2012). These characteristics make
"true" salamanders an exceptional biological system to extend our understanding of the evolution
reproductive modes and the modularity of life history strategies in amniotes.

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334 *Negligible actuarial senescence in true salamanders*

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We observed negligible actuarial senescence in the three species of true salamanders considered in
our study. The mortality rate was relatively stable and weakly affected by age in the three taxa and
the two populations of *S. salamandra*. This mortality pattern markedly differs from age-dependent
mortality rates found in various species of anurans and newts (using capture-recapture data with
relatively similar sample size, and a similar modeling approach), which may experience a sharp,
early senescence (Miller et al. 2014, Colchero et al. 2019; but also see Jones et al. 2014). The
detection of actuarial senescence in other species using similar modeling tools (Miller et al. 2014,
Colchero et al. 2019) indicates that the negligible senescence in true salamanders is not a
methodological artefact. It has previously been suggested that detecting senescence would be
difficult in wild animals because high levels of mortality would remove individuals from the
population before they start to senesce (Kirkwood & Austad 2000). However, by revealing a great
diversity of senescence patterns, studies using capture-recapture data collected across a broad range
of taxa showed that this assumption was untrue (Jones et al. 2008, 2014; Colchero et al. 2019; see also Jones & Vaupel 2017 for a review). Furthermore, Colchero's model has proven to be particularly efficient for detecting senescence when it is actually present (Colchero & Clark 2012, Colchero et al. 2012). Simulations showed that the model is able to detect senescence when the study period is equal or longer than the mean lifespan in the population (Colchero & Clark 2012), which was the case in the four datasets considered in our study.

A long lifespan, a high level of iteroparity, and a low reproductive effort appear to be closely associated with negligible actuarial senescence in the three species of true salamanders considered in our study. This pattern is congruent with the results of Jones et al. (2008) showing that senescence rate is negatively correlated with generation time and age at primiparity, and is positively associated with maximum fecundity in endotherm vertebrates; the opposite relationships were detected with the age at senescence onset. Interestingly, our results suggest an absence of trade-off between senescence and offspring production in true salamanders. Although they display large variation in annual offspring numbers, the three species experience negligible senescence. This seems to indicate a partial decoupling of senescence and reproductive effort whose the variation is rather associated with species-specific reproductive mode (oviparity, lecithotrophic viviparity, and matrotrophic viviparity). However, our study focused on a limited number of salamander species and further investigations are required to examine in details covariation between senescence (speed and age at onset of senescence) and life history traits at the clade level.

The negligible senescence of salamanders likely relies on their high regenerative capacities. Contrary to other amniotes, salamanders are able to retain near perfect regeneration of most organs and appendages (e.g., spinal cord, heart, brain, skin, digit, and lens) well into adulthood (Seifert & Voss 2013). Although almost no studies have tested these abilities in old animals (Seifert & Voss 2013), their great potential for tissue repair and regeneration likely probably allow true salamanders to escape actuarial senescence. In parallel, although we did not detect size-dependent survival in *L. fazilae*, an indeterminate growth (Jones & Vaupel 2017) could also contribute to the negligible senescence reported in our study. Furthermore, a low body temperature and a low metabolic rate (Hulbert et al. 2007, Flouris & Piantoni 2015) might also limit actuarial senescence.

Our results also showed that negligible senescence is a consistent pattern at both intraspecific and interspecific levels in true salamanders (at least in the species considered in this study). This indicates that negligible senescence may be a phylogenetically conserved trait within a clade containing species that have diverged a long time ago (several million years; Weisrock et al. 2006). These results suggest a strong genetic determinism in aging mechanisms and the existence of orthologous genes involved in the repression of actuarial senescence in urodeles.
However, the genomic architecture of life history components as senescence rate and onsets remains poorly understood, except in few model species (e.g., *Drosophila*: Remolina et al. 2012, Ivanov et al. 2015; human: Deelen et al. 2013). The recent development of powerful genomic tools should allow identifying candidate genes and gene networks involved in senescence regulation.

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## Conclusion

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Negligible actuarial senescence is highlighted in a growing number of taxa, mainly ectotherms (e.g., corals, hydras, and amphibians; Jones et al. 2014). These cases have been considered for a long time as exceptions or the product of methodological artefacts, in light of senescence having been presented as a nearly ubiquitous phenomenon in the living world. We argue that this representation was partly due to a taxonomic bias where the study of senescence has for many years been focused on endotherm vertebrates (mainly mammals) with reduced regenerative capacities at adult stages (Seifert & Voss 2013). The regenerative capacities of true salamanders, and urodeles in general, likely explains why these small ectotherm amniotes (the body mass of the largest true salamanders is ≈ 50g) have lifespans similar to that of large endotherm amniotes (e.g., ungulates, large birds) and undergo a negligible actuarial senescence contrary to most vertebrates including humans (Jones et al. 2014).

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<figure><img src="image_3.png" /></figure>

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**Fig.1.** Annual adult survival (and standard errors) in three species of salamanders from the Western Palearctic. (A) Map showing the populations of *Lyciasalamandra fazilae* (in red), *Salamandra salamandra* (in blue), and *Salamandra perspicillata* (in violet) considered in this study. Note that data of only one population of *Salamandra perspicillata* was available for the present study (the southernmost population on the map). (B) Survival of small and large adults of *Lyciasalamandra fazilae* and their standard errors (model-averaged) estimated using our survival and recruitment models. (C) Survival estimates of *Lyciasalamandra fazilae* (from this study) and *S. salamandra* and *S. perspicillata*, which are extracted from two previous capture-recapture studies (Cayuela et al. 2017, Angelini et al. 2010, respectively). The phylogenetic tree is the one presented in Weisrock et al. 2006.
<figure><img src="image_4.png" /></figure>

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**Fig.2.** Survival until age *x* (full lines) and their 95% CI (broken lines) in three salamanders of Western Palearctic. The vertical line indicates the length of the capture-recapture survey.

602
<figure><img src="image_5.png" /><figcaption>**Fig.3.** Mortality rate at age *x* (full lines) and their 95% CI (broken lines) in three salamanders of Western Palearctic. The vertical line indicates the length of the capture-recapture survey.</figcaption></figure>