# Contrasted effects of temperate forest closure on snake demography

G Billy, C Barbraud, X Bonnet

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## To cite this version:

G Billy, C Barbraud, X Bonnet. Contrasted effects of temperate forest closure on snake demography. Ecosphere, 2025, 16, 10.1002/ecs2.70468. hal-05415950

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# Contrasted effects of temperate forest closure on snake demography

G. Billy

C. Barbraud

X. Bonnet

Centre d'Etudes Biologiques de Chizé,
UMR-7372, CNRS-La Rochelle Université,
Villiers en Bois, France

**Correspondence**

X. Bonnet
Email: bonnet@cebc.cnrs.fr

**Handling Editor:** Robert R. Parmenter

**Abstract**

Habitat modification is the main threat to biodiversity, but other causes are involved, such as climate change or pollution. To optimize conservation efforts, it is crucial to determine their respective contributions. An effective approach to disentangle causalities is to set up comparative or experimental monitoring in the field. In a temperate forest classified as an integral nature reserve, left unexploited, tree growth led to canopy closure and the progressive disappearance of semi-open woodlands and associated thermophilic species. Past logging provided a semi-experimental setting with contrasting patches in terms of canopy closure. A long-term capture-mark-recapture study of two snake species (1995-2021), one thermophilic and the other less so, revealed which demographic parameters were affected and established a link between habitat closure and population decline. For the most thermophilic species (*Hierophis viridiflavus*), rapid increases in canopy cover drastically reduced the survival probability of very young individuals, neonates and snakes a few months old, likely by depriving them of essential thermophilic prey (i.e., small lizards). Juveniles and adults that feed mainly on rodents and less on thermophilic lizards were less affected. For the least thermophilic snake species (*Zamenis longissimus*) where all age groups feed on rodents, habitat closure had no major effect on survival. Importantly, open woodlands remained favorable for both species. Although closing habitat was detrimental to *H. viridiflavus*, we predict that the survival of *Z. longissimus* will also drop as the forest closure approaches 100%. Canopy closure and the disappearance of shrubby habitats are the main factors responsible for the decline of forest snakes. A lack of management in temperate forests may not be the best option to maintain healthy reptile populations.

**KEYWORDS**

Aesculapian snake, capture-mark-recapture, *Hierophis viridiflavus*, strictly protected forest, survival, whip snake, *Zamenis longissimus*

This is an open access article under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2025 The Author(s). *Ecosphere* published by Wiley Periodicals LLC on behalf of The Ecological Society of America.
# INTRODUCTION

Population dynamics and viability are influenced by envi-
ronmental factors in complex ways (Royama, 1992;
Turchin & Taylor, 1992). Monitoring abundances is the
first step in exploring population dynamics, in particular
to uncover possible relationships between environmental
variations and population trends (Turchin, 2003).
However, simply reporting abundance is generally not
sufficient to identify the factors involved in population
changes (Williams et al., 2002), and even less to evaluate
their respective roles (e.g., Anderson et al., 2013; Skalski
et al., 2005). Understanding population fluctuations
requires an assessment of the demographic parameters
underlying population growth rates, often according to
age, sex, or individual states, and assessing which envi-
ronmental variables affect these demographic parameters
(Nott & Desante, 2002; Sibly et al., 2003; Williams
et al., 2002). This is also important to forecast demo-
graphic trends and propose guidelines for species man-
agement and conservation (Caswell, 2001; Jenouvrier
et al., 2014). For example, demographic modeling using
mark-recaptures has shown that trophy hunting, which
targets adult male lions and disrupts their social function-
ing, was the main cause of their decline in Zambia
(Rosenblatt et al., 2014). Another study of the demo-
graphic parameters of a toad population exposed to an
emerging disease revealed that the compensatory effects
of survival and recruitment rates were important for hab-
itat management (Muths et al., 2011). Mark-recapture
studies are thus essential to disclose causalities between
environmental factors and population decline.

Although long-term individual capture-mark-recapture
(CMR) is a powerful method (Williams et al., 2002), the
experimental approach based on the use of field replicates is
often the only way to isolate and compare underlying causes
without ambiguity (Hurlbert, 1984). However, in practice,
combining long-term field population monitoring with an
experimental approach is challenging, because it is generally
impossible to have experimental natural systems in which a
factor of interest could vary between replicated populations.
One option is to find a quasi-experimental design in which
several populations are exposed to variations in a key envi-
ronmental factor (or a few factors) (e.g., Butsic et al., 2017;
Cunningham & Lindenmayer, 2017; Gibbs et al., 2010).

In this study, we used such a quasi-experimental
design in which a major habitat feature, forest canopy
closure, varied in a contrasting way between forest plots
that harbor different snake populations. In the temperate
forest in western France that was studied, past logging
has created sets of open, semi-open, and closed forest
plots that have changed in different ways since the forest
was classified as a strict biological reserve that prevented

forest exploitation and management. The different plots
host more than 20 (sub-) populations of two snake spe-
cies monitored by CMR for over 25 years, both before
and after the forest was classified as a strict biological
reserve, generating fortuitous replicates spread in the for-
est. It is then possible to compare population changes
and the underlying demographic parameters as a func-
tion of the initial state and rate of canopy closure. This
situation provides a unique opportunity to examine the
impact of changes in forest habitats (i.e., change in
canopy cover) on the functioning of reptile popula-
tions. Many snake species are declining worldwide
(Pomara et al., 2014; Reading et al., 2010; Zipkin
et al., 2020). Because 18% of the world forest surface is
under protected areas (FAO, 2020) and because forests
contain most of the terrestrial biodiversity (Brockerhoff
et al., 2017; Gibson et al., 2011; Pillay et al., 2021), exam-
ining the impact of increasing canopy cover in a strictly
protected forest on the maintenance of reptile
populations is important.

The primary hypotheses linking canopy cover to rep-
tile populations, based on the relationship between ambi-
ent conditions, body temperature, and metabolism in
ectotherms, are relatively straightforward (Seebacher &
Franklin, 2005). In temperate regions, exposure to the
sun is important during energy-demanding physiological
periods such as digestion (Bogert, 1949; Burger et al.,
2004), vitellogenesis, and pregnancy (Bonnet & Naulleau,
1996a; Moniz et al., 2024). A closed canopy that deprives
most reptiles of thermoregulation options is associated
with low population densities compared with forests that
also contain open habitats (Duchesne et al., 2023;
Greenberg, 2001; Huang et al., 2014; Jofré et al., 2016).
Moreover, experimental canopy removal leads to snake
population increases (Bonnet et al., 2016; Pike et al.,
2011a, 2011b; Webb et al., 2005). However, these findings
based on abundances do not allow identifying which
demographic parameters were involved and crucial ques-
tions remain unanswered. For example, does increasing
canopy cover have an impact on a particular sex or age
class? Does it affect adult or immature survival rates or
recruitment rates? Canopy cover may target a specific
category of individuals, such as reproductive females
(Robson & Blouin-demers, 2021; Shoemaker & Gibbs,
2010). Reproduction can be affected by the lack of open
areas needed to heat egg-laying sites or used by pregnant
females for thermoregulation (Johnson et al., 2016;
Shine & Bonnet, 2009). Alternatively, closed habitats may
remove key trophic resources for reptiles, such as ther-
mophilic prey (e.g., many insects; Buckley, 2020;
Warren & Key, 1991) possibly affecting all age classes. It
is also possible that the lack of an understory layer in
high and mature forests exposes reptiles to predation
(Duchesne et al., 2022; McGregor et al., 2015). All these environmental factors can act in isolation or through complex interactions, and may well act in a particular way for the different species concerned (He et al., 2013; Sinclair et al., 2016).

Snakes are suitable organisms to answer the ques-
tions above. Many are relatively sedentary and
philopatric predators that depend on specific microhabi-
tats (Brischoux et al., 2009; Clark et al., 2008; Nordberg
et al., 2021). Therefore, environmental changes on a local
scale should have a direct and unequivocal impact on
their demographic parameters. Furthermore, snakes
exhibit major ecological divergences between the sexes
and among age classes, making it possible to examine
how changes in microhabitat affect different categories of
individuals (Shine, 2003).

The two snake species monitored in this study exhibit contrasting ecologies and physiologies (Lelièvre et al., 2010, 2011, 2012). The western whip snake (*Hierophis viridiflavus*) is a highly thermophilic racer that maintains high body temperatures, notably via sun basking. In contrast, the Aesculapian snake (*Zamenis longissimus*) is largely a thermo-conforming species that can be active under a wide range of body temperatures; sun basking is less important. The more thermophilic species should be more sensitive to increasing canopy closure. Long-term monitoring of population abundance showed that canopy closure led to rapid and severe declines in the whip snake populations and less pronounced declines in the Aesculapian snakes (Billy et al., 2024). However, the underlying demographic processes remain to be identified. Therefore, the main objectives of this study are to (1) estimate sex-, age-, and habitat-specific demographic parameters for each snake species to establish causal links between habitat change and population decline; and (2) fill the knowledge gap concerning the influence of natural habitat modifications on snake demographic processes.

MATERIALS AND METHODS

Study site

The Chizé forest (4775 ha; 47–101 m above sea level; 46.145° N, –0.427° E) is located in western France. This temperate forest, mainly deciduous (genus *Quercus* 38%, *Fagus sylvatica* 35%, other deciduous trees 17%), was exploited for timber production through a system of rotational harvesting of geometric plots (5–20 ha parcels). In recent decades, some plots have not been harvested; others have been completely cleared; and still others have been partially harvested. Two powerful storms hit the

forest in December 1999 (Rivière et al., 2010); 200,000
trees were felled by very strong winds (the equivalent of
20 years' timber harvest), and 800 ha were opened
up. The forest reached its maximal opening stage in early
2000. Since then, timber harvesting in the southern half
of the Chizé forest (i.e., a hunting reserve and the future
protected area, see below) has ceased, allowing trees to
continue to grow (Vild et al., 2013). The year 2000 thus is
a milestone in the forest's history, in terms of both man-
agement and canopy closure.

In September 2006, the protection status of most of
the hunting reserve (2579 ha; ~99%) was raised to the
maximal level: Strict Nature Reserve (SNR) or Integral
Biological Reserve (RBI, 1a IUCN category; Dudley,
2008). The aim of this SNR forest, one of the largest in
Europe, is to maintain and even increase biodiversity: the
official decree (no. DEVN0650590A) states that the main
objective is to "...allow the natural evolution of ecosystems
to express itself freely, in order to increase and maintain
biodiversity..." Since then, the canopy has gradually
closed over all the plots, except for two small meadows
(enclaves) of 15.1 and 6.4 ha not classified as SNR, which
are kept open by shredding. As a result, patchy logging
prior to 2000, followed by a definitive cessation of log-
ging, resulted in contrasting canopy closure dynamics
between forest plots. The legacy of contrasted timber
harvesting by plots before 2000, along with the two small
open enclaves, offered a quasi-experimental design to
survey the influence of canopy closing on animal
populations.

Habitat categories and canopy closure

On the basis of satellite images and ground photo-
graphy, three types of habitats, closed, open, and
semi-open were considered to assess changes in vegeta-
tion cover trajectories between 2000 and 2020 (details
in Billy et al., 2024). In closed plots (C), canopy covered
71%-100% of the surface, forming a dense overstory. In
open plots (O), the herbaceous layer with small bushes
dominated, canopy covered 0%-30% of the surface. In
semi-open plots (i.e., Intermediate I), the canopy
represented 31%-70% of the surface area; spaced trees
(or small groups of trees) were mixed with herbaceous
and bushy patches. In closed plots, the ground vegeta-
tion is sparse and the possibilities for sun basking are
limited for snakes. Open and semi-open plots offer
abundant refuges (thick vegetation on the ground) and
opportunities for snakes to bask in the sun, as demon-
strated by radio-tracking (Lelièvre et al., 2010, 2013).
As this study focuses on contrasting trajectories of
habitat change over two decades, we have considered three main dynamic categories of plot:

1. Open–Open (O–O): Canopy never covered more than 30% of the surface during the 20 years of forest survey. Canopy cover changes were limited. Only the two enclaves belonged to this category.

2. Closed–Closed (C–C): Canopy always covered more than 70% of the surface during the 20 years, gradually reaching 100% (as expected following wood harvesting cessation). Canopy cover changes were relatively limited, however.

3. Open–Closed (O–C): Canopy cover strongly increased over the course of the study and was associated with marked changes. In most cases, open or semi-open plots (O or I) became closed plots (>70% closeness); in a limited number of plots, canopy cover shifted from open to semi-open status (Table 1).

Compared to the two first plot categories (O–O) and (C–C), plots from the third category (O–C) underwent the greatest changes in terms of canopy closure and therefore ground vegetation decrease, particularly in the plots that were initially the most open (canopy cover shifting from ≤30% to >70%).

## Snake species

The western whip snake and the Aesculapian snake are medium-sized snake species (adult snout vent length ~0.9 m; Bonnet et al., 1999). In the studied forest, these colubrids are syntopic, both depend on microhabitats where they find their main prey (voles, field mice, and

<table><caption>TABLE 1 Changes in canopy closure and surface area of the three categories of plots in the Chizé forest reserve.</caption><thead><tr><th>Plot category</th><th>Surface (ha)</th><th>Habitat in 2000</th><th>Habitat in 2020</th></tr></thead><tbody><tr><td>O–O</td><td>28.0</td><td>Open</td><td>Open</td></tr><tr><td>C–C</td><td>1884.2</td><td>Closed</td><td>Closed</td></tr><tr><td>O–C</td><td>335.6</td><td>Open</td><td>Closed</td></tr><tr><td>O–C</td><td>315.8</td><td>Intermediate</td><td>Closed</td></tr><tr><td>O–C</td><td>97.6</td><td>Open</td><td>Intermediate</td></tr></tbody></table>

Note: O–O: A small area of forest (two plots) was kept open by shredding, with canopy cover remaining below 30% from 2000 to 2020. C–C: Most of the forest remained closed between 2000 and 2020 (canopy closure increased from >70% to 100% in many plots). O–C: The open and semi-open habitats initially considered open or intermediate (cover: 0%–30%; 31%–70%, respectively) have undergone significant closure; a limited area has changed from open to intermediate. For the sake of brevity, the three subcategories that have undergone radical changes have been grouped together in the O–C category.

shrews); *H. viridiflavus* also regularly feeds on reptiles (~20%) and *Z. longissimus* on nesting birds (~10%) (Lelièvre et al., 2012). Importantly, there is a marked change in the ontogenic diet of *H. viridiflavus* regarding the most thermophilic prey (i.e., wall lizards and green lizards) versus less thermophilic ones (endothermic mammals and birds). In this species, small lizards (Appendix S1: Figure S1) account for more than 80% of the prey consumed by neonates; this proportion falls to 20% in adults and is intermediate in juveniles (32%). In contrast, *Z. longissimus* neonates feed mainly on small mammals (67%), as do juveniles and adults (>90%) (Lelièvre et al., 2012).

These two species have contrasting ecophysiologies, reflected in differences in the way snakes use microhabitats in the studied forest (e.g., an individual can either remain in the shade in a bush or bask on top of it), and contrasting thermoregulatory behaviors and locomotor performances. *H. viridiflavus* is a terrestrial thermophilic racer that selects high body temperature; *Z. longissimus* is a partly arboreal, relatively slow-moving, highly secretive, and largely thermo-conformer snake (Lelièvre et al., 2011, 2013). *H. viridiflavus* is more dependent on open microhabitats compared with *Z. longissimus*, which is more adapted to arboreal strata.

## Snake population monitoring

Snakes are very secretive animals, especially in woodland areas (Steen, 2010). Networks of artificial shelters increase detection rates and standardize field procedures (Bonnet et al., 2016). Since 1995, a network of geo-located corrugated concrete slabs (120 × 0 cm) has been deployed in the forest; snakes were almost impossible to detect without this system (Billy et al., 2024; Bonnet et al., 1999). The network of slabs is discontinuous and composed of 11 sub-networks (= 11 searching sites; Appendix S1: Figure S2), each one associated with one of the three plot categories. The mean distance (±SD) among sub-networks (taking the middle of each site) was 2873 ± 1227 m and among the three plot categories was 2767 ± 790 m (range 1937 to 4001). The shortest distance between two slabs at two different sites was 25 m and the longest was 5840 m. The total number of slabs and surveys increased over time, reaching a total of 798 slabs and 117 surveys in 2021 (details in Billy et al., 2024).

During a given routine survey of a sub-network, the slabs were successively lifted. Most of the time, the 11 sub-networks could not be checked during a single day; in general, it took a week to sample the entire network. Fieldwork was performed during the active season of the two snake species, usually from April to October.
Individuals were sexed, measured (snout to vent length, SVL), photographed, permanently marked (scale rows were superficially burned following a code, triggering a stable color change), and released at the exact place of capture (Bonnet et al., 2016).

To test the influence of habitat closure on demographic parameters, it was essential to examine whether the snakes moved from one sub-network to another, possibly moving from one habitat category to another, which would confound the analyses in the event of frequent switching. We thus inspected the entire CMR dataset to record the number of individuals shifting across sub-networks or across the habitat categories defined above (O–O, C–C, and O–C). The number of switching individuals was negligible (4% across sub-networks, 0.4% across categories in *H. viridiflavus*, and 2% across sub-networks, 0% across categories in *Z. longissimus*; Billy et al., 2024). This very low rate of exchange of individuals between sub-networks suggests a demographic functioning based on subpopulations (although gene flow is likely). For the sake of simplicity, we will refer to each subpopulation as a “population” and each individual was assigned to a single habitat category in which it was originally captured.

## Modeling demographic parameters

Each species was analyzed separately. We used mark-recapture data collected between 1995 and 2021 for both species to estimate demographic parameters, covering several years before the forest was largely opened in early 2000. This represented 997 individual capture histories for *H. viridiflavus* and 1553 for *Z. longissimus* (Billy et al., 2025). The frequency of snake captures under slabs was bimodal: It was maximal in spring, dropped in summer during dry periods, and then increased again in autumn (to a lesser extent than spring). Therefore, for each year, two capture sessions were selected: April to June (i.e., spring) and September to October (i.e., autumn). This breakdown into two capture sessions allowed the estimation of seasonal survival probability with a spring-summer and an autumn-winter survival. An unequal time interval vector was used to account for the different time intervals between the two sessions: 5 months (April-August; spring-summer interval) and 7 months (September-March; autumn-winter interval). The annual survival estimates corresponded to a survival probability calculated over 5 months of active life. This represents the period from the end of hibernation to the end of summer, that is, most of the active period, in which case the annual survival estimate is consistent with the annual survival reported in other studies

(King et al., 2018). This period corresponds to the time when snakes often bask in the sun to digest prey or shed their skin. It is also the time when they take great risks in order to mate and/or travel to and from egg-laying sites (Bonnet et al., 1999). Thus, many factors affect survival during this time, whereas during hibernation snakes remain sheltered.

We considered three age classes: (1) neonates and individuals a few months old (all named neonates for conciseness), (2) juveniles, and (3) adults (Appendix S1: Figure S3), which were defined based on body size as described in Appendix S1: Table S1. To determine size-based age classes, we used the morphological traits and evidence for sexual maturity such as the presence of sperm, follicles, or eggs:

### Neonates (Nn)

A few females ready to lay eggs were kept in captivity for a few days to collect their clutch. After incubation, the hatchlings were measured (usually in late August–September). We used these data to determine the mean SVL and body mass of neonates. Any snake captured under a slab that met these criteria was then labeled as a neonate (Appendix S1: Figure S3, Table S1). Importantly, a snake categorized as neonate will have to exit this state after its first spring (i.e., after June). In neonates, the sexes were pooled because sexual dimorphism at birth was small (e.g., relative tail length differs) and no niche divergence between the sexes was detected (X. Bonnet, unpublished data).

### Adults (Ad)

The smallest female (SVL) palpated with growing follicles or eggs and the smallest male (SVL) that produced spermatozoids (determined using cloacal smears; Bonnet & Naulleau, 1996b) provided the lower limit for sex-specific maturity.

### Juveniles (Ju)

Snakes with an intermediate body size between neonates and adults were considered as juveniles.

We used multistate mark-recapture (MSMR) models to examine how sex, habitat (O–O, O–C, and C–C), and age classes influenced demographic parameters. We considered the three age classes as states, and sex and habitat as groups. Individuals could move unidirectionally
between states between successive capture sessions (Appendix S1: Section S1, Figure S4). Four parameters were estimated: (1) The recapture probability (C) defined as the probability that an individual alive at session *t* was captured. (2) The initial state (IS) defined as the initial probability of individuals to be assigned to one state (i.e., age class). (3) The age class transition probability (T) defined as the probability that an individual in age class *r* at session *t* moves to age class *s* at session *t* + 1, conditional on survival from *t* to *t* + 1. (4) The apparent survival probability (S) defined as the probability that an individual survives from session *t* to *t* + 1, and it returns to the sampling area (Sandercock, 2020). For brevity, we will refer to survival hereafter.

To allow parameter estimation and identifiability several constraints were used. First, initial state, survival, and transition probabilities were set as constant through time (i.e., they did not vary between sessions). However, they were allowed to vary between sexes, states (i.e., age classes), and habitats. Second, recapture probabilities were constrained to not vary between sessions but were allowed to vary between seasons (detailed below in *Model selection*), sexes, habitats, and states. Therefore, three states (Nn, neonate; Ju, juvenile; and Ad, adult) and six groups (2 sexes × 3 habitat categories: FOO, FCC, and FOC stand for females respectively in O–O, C–C, and O–C plot category; similarly for males with MOO, MCC, and MOC) were implemented to analyze the demographic traits of each species.

## Model selection

Starting with the modeling of recapture probabilities, we included all groups (i.e., sex, habitat) and states, while looking for the more complex time structure that allowed the estimation of all mathematical parameters (i.e., full rank model). We ended up with a full rank starting model. From this full rank starting model, we used a step-by-step model selection approach to obtain the best-supported model. Then, we modeled initial state probabilities while retaining the selected structure for recapture probabilities, and so on until modeling survival probabilities, which provided the best model structure. The step-by-step approach is detailed below.

For recapture probabilities, we first tested the season effect by grouping all spring sessions into a single spring season and all autumn sessions into a single autumn season. We called “season effect” the possible separate effect of spring and autumn on recapture probability estimates. During cold autumns, snake activity was shortened and fewer snakes were recaptured. Moreover, fewer fieldworkers were available to conduct surveys in autumns.

Thus, we suspected snake recapture probability to be lower in autumn sessions compared to spring sessions. We also tested a “period effect” by grouping all spring sessions between 1995 and 2013 and between 2014 and 2021. The distinction between these two periods was motivated by the fact that population monitoring became more standardized since 2013. Then, we tested the effect of state, plot categories (later called habitat for convenience), and sex on recapture probability. When we tested for a state effect, we tested whether recapture probabilities differed among states, but we also tested whether adult recapture probabilities differed from those of neonates and juveniles pooled (i.e., adults vs. non-adults), or whether neonate recapture probabilities differed from those of juveniles and adults pooled (i.e., neonates vs. non-neonates).

Keeping the best structure for recapture probabilities, we then explored habitat and sex effects on initial state probabilities. We then modeled the effects of state, habitat, and sex on transition probabilities. Finally, we tested for state, habitat, and sex effects on survival probabilities.

For model selection and hypothesis testing, we used an information theoretic approach, based on ecologically relevant hypotheses, and based on the correction for small sample sizes to prevent overfitting (corrected Akaike information criterion [AICc]) (Anderson & Burnham, 2002). The sample sizes used for the AICc are available in Appendix S1: Table S2. During model selection, we retained the model whose AICc was 2 units lower than its concurrent model. When the AICc difference between two models was less than 2, we explored the difference in deviance (Δdev) and the difference in the number of parameters K multiplied by two (Δ2K) (Arnold, 2010; Leroux, 2019). If Δ2K < Δdev, we selected the model with the lower deviance, and when Δ2K ≈ Δdev, we selected the most parsimonious model (i.e., which used fewer parameters).

From the best-supported model, we also tested whether linear trends occurred in survival parameters. For this purpose, we built models where survival $\Phi$ was modeled as $\logit(\Phi) = \alpha + \beta \times T$, where $\alpha$ is an intercept parameter, $\beta$ is a slope parameter, and $T$ is a linear temporal trend. When $\beta > 0$ the parameter increases through time, whereas it decreases when $\beta < 0$. We used ANODEV to test for linear trends (Grosbois et al., 2008). In case of a significant ANODEV test, the CI of the slope was checked. If 0 belonged to the CI of the slope parameter, we rejected the hypothesis of a trend even if the ANODEV test was significant. Linear trends in survival were tested for each habitat and state retained in the best model.

Beforehand, we carried out an in-depth selection of more than 150 models tested for species (not presented
here). For clarity of interpretation, and to favor the con-
tribution of biological and ecological parameters, we
made a more standardized (simpler) selection of models.
To test the effect of a factor (i.e., state, habitat, sex), we
compared the model including the factor versus the
model excluding it, all other things being equal. If
the absence of the factor improved the model
(i.e., lowered AICc), the factor was irrelevant and was
not considered further. Conversely, if the absence of
the factor resulted in an increase of at least two units
in the AICc (significant deterioration), it was retained.
All models were built in program E-SURGE (Choquet,
Rouan, & Pradel, 2009). To detect the local minimum
of the likelihood function, we ran each model with
10 random initial parameter values (using option
Multiple random in E-SURGE) and carried out 3 cycles
of 200 iterations each to avoid convergence difficulties.

Goodness-of-fit test

To test whether the MSMR models fitted the data, the
goodness-of-fit (GOF) tests for multistate models
(Pradel et al., 2003) were performed using the software
U-Care (Choquet, Lebreton, et al., 2009). We ran the
test on the JollyMoVe umbrella model for multistate
(Brownie et al., 1993). Outcomes of the GOF tests were
not significant in both species (χ² = 76.515, df = 211,
p = 1 for H. viridiflavus and χ² = 131.197, df = 282,
p = 1 for Z. longissimus), therefore suggesting no lack
of fit (Appendix S1: Table S3).

RESULTS

Modeling demographic parameters

In *H. viridiflavus*, model selection suggested that recap-
ture probabilities varied between seasons (higher in
spring vs. autumn) and states (adults were more likely to
be recaptured, especially in spring during the mating
period) (Tables 2 and 3). Initial state proportions varied
between habitat categories (i.e., O–C, C–C, and O–O
plots) (Table 2): In O–C plots, snakes first captured were
more often adults; in C–C plots, they were more likely to
be neonates; and in O–O plots, juveniles and adults
were more represented compared to neonates (Table 3).
State transition probabilities of *H. viridiflavus* were not
influenced by any of the factors tested, that is, the proba-
bility for a neonate to become a juvenile (or an adult; this
later probability was particularly low), or for a juvenile to
become an adult, was not dependent on habitat or sex
(Table 2).

*H. viridiflavus* survival varied between states and hab-
itats (Tables 2 and 3). Juveniles and adults had similar
survival, which was higher than neonate survival.
Habitat had an important effect on neonate survival: In
C–C plots, neonates had a zero apparent survival (which
excluded them from the transition stage). This estimate
was consistent with the total absence of recapture of neo-
nates in the C–C plots (38 neonates captured, but none
recaptured). Neonate survival was similar in O–C and
O–O plots (5-month survival ≈ 0.59 [Figure 1, Table 3],
equivalent to an annual survival of 0.31 [Appendix S1:
Table S4]). In O–C plots, neonate survival decreased
over time (ANODEV test = 7.778, *p* < 0.05; slope
[SE] = −0.220 [0.121]). No other temporal trend was
detected in survival in this species. Mean survival of
juveniles and adults was highest in O–O plots and low-
est in C–C plots, being intermediate in O–C plots
(Table 3, Figure 1).

In *Z. longissimus*, model selection suggested that recapture probabilities were influenced by season (higher in spring vs. autumn), state (adults were more likely to be recaptured), and sex (males were more likely to be recaptured than females) (Tables 4 and 5). Initial state values varied between habitats and sexes (Table 4): In O–O and O–C plot categories, adult males were more likely to be represented at first capture (Table 5). As observed in *H. viridiflavus*, state transition probabilities were not influenced by the factors tested (Table 4). Regarding survival, two models were favored (Table 4). Both indicated an effect of state, neonate survival being much lower compared to juveniles and adults. However, there was uncertainty on the effect of habitat on neonate survival; one model suggested no effect (Table 4), while the other suggested higher survival in O–C plots than in other plots (Tables 4 and 5). In O–O plots, survival of non-neonates (i.e., juveniles and adults pooled) increased over time (ANODEV test = 9.886, *p* < 0.05; slope [SE] = +0.071 [0.026]). No other temporal trend was detected on survival in this species.

DISCUSSION

Intensive CMR monitoring of multiple subpopulations of
two snake species over 27 years in a semi-experimental
forest enabled us to identify key demographic parame-
ters underlying the strong decline (~60% drop, Billy
et al., 2024) caused by canopy closure. Notably, abun-
dances of *H. viridiflavus* decreased sharply over time most
probably due to the very low survival of neonates in
closed plots, while in *Z. longissimus*, abundance and sur-
vival were much less affected, even long after the decline
of *H. viridiflavus*.
<table><caption>TABLE 2 Modeling the effects of sex, habitat, and state (i.e., age classes) on demographic parameters for *Hierophis viridiflavus* in the Chizé forest between 1995 and 2021.</caption><thead><tr><th>Main steps</th><th>Model</th><th>Season</th><th>Period</th><th>Nn</th><th>Ju</th><th>Ad</th><th>Habitat</th><th>Sex</th><th>Par</th><th>Dev</th><th>AIC<sub>c</sub></th></tr></thead><tbody><tr><td rowspan="10">C</td><td>C1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>102</td><td>5037.63</td><td>5256.75</td></tr><tr><td>C2</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>66</td><td>5488.34</td><td>5625.83</td></tr><tr><td>C3</td><td>1</td><td>0</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>84</td><td>5051.89</td><td>5230.03</td></tr><tr><td>C4</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>60</td><td>5083.15</td><td>5208.26</td></tr><tr><td>C5</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>72</td><td>5053.00</td><td>5204.41</td></tr><tr><td>C6</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>72</td><td>5081.74</td><td>5233.15</td></tr><tr><td>C7</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td><strong>52</strong></td><td><strong>5067.41</strong></td><td><strong>5175.25</strong></td></tr><tr><td>C8</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>60</td><td>5056.97</td><td>5182.09</td></tr><tr><td>C9</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>56</td><td>5058.76</td><td>5175.21</td></tr><tr><td rowspan="4">IS</td><td>C7_IS1</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>1</td><td>52</td><td>5067.41</td><td>5175.25</td></tr><tr><td>C7_IS2</td><td></td><td></td><td></td><td></td><td></td><td>0</td><td>0</td><td>42</td><td>5174.62</td><td>5261.11</td></tr><tr><td>C7_IS3</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>0</td><td><strong>46</strong></td><td><strong>5077.10</strong></td><td><strong>5172.10</strong></td></tr><tr><td>C7_IS4</td><td></td><td></td><td></td><td></td><td></td><td>0</td><td>1</td><td>44</td><td>5170.06</td><td>5260.80</td></tr><tr><td rowspan="4">T</td><td>C7_IS3_T1</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>1</td><td>46</td><td>5077.10</td><td>5172.10</td></tr><tr><td>C7_IS3_T2</td><td></td><td></td><td></td><td></td><td></td><td>0</td><td>0</td><td><strong>31</strong></td><td><strong>5083.30</strong></td><td><strong>5146.66</strong></td></tr><tr><td>C7_IS3_T3</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>0</td><td>37</td><td>5081.05</td><td>5156.99</td></tr><tr><td>C7_IS3_T4</td><td></td><td></td><td></td><td></td><td></td><td>0</td><td>1</td><td>34</td><td>5081.69</td><td>5151.32</td></tr><tr><td rowspan="7">S</td><td>C7_IS3_T2_S1</td><td></td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>31</td><td>5083.30</td><td>5146.66</td></tr><tr><td>C7_IS3_T2_S2</td><td></td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>19</td><td>5109.60</td><td>5148.11</td></tr><tr><td>C7_IS3_T2_S3</td><td></td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>1</td><td>25</td><td>5101.25</td><td>5152.14</td></tr><tr><td>C7_IS3_T2_S4</td><td></td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>25</td><td>5095.17</td><td>5146.06</td></tr><tr><td>C7_IS3_T2_S5</td><td></td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>15</td><td>5117.11</td><td>5147.44</td></tr><tr><td>C7_IS3_T2_S6</td><td></td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>19</td><td><strong>19</strong></td><td><strong>5101.49</strong></td><td><strong>5140.01</strong></td></tr><tr><td>C7_IS3_T2_S7</td><td></td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>17</td><td>5113.64</td><td>5148.05</td></tr></tbody></table>

Note: Model selection was conducted in the following order: recapture probability (C), initial state (IS), state transition (T), and survival (S). Each model tested is labeled with a capital letter and a number. Starting model (C1) corresponds to the full rank model for recapture probability. Subsequently, at each step, one or several effects are removed or put back. For example, removing season and period effects on recapture probability led to a model with a higher corrected Akaike information criterion (AIC<sub>c</sub>) (model C2), but removing only the period effect lowered the AIC<sub>c</sub> (model C3). Therefore, state effect was tested relative to the improved model C3, and so forth. The best model obtained for recapture probability is indicated in bold. It was retained for the next step (IS). The same process was done for T and S. When modeling recapture probability, IS and T and S included all groups and states. Thus, the first model of each next step is identical to the best model retained at the corresponding previous step (i.e., C7 = C7_IS1; C7_IS3 = C7_IS3_T1; C7_IS3_T2 = C7_IS3_T2_S1). Abbreviations: 0, absence of factor; 1, presence of factor; Ad, adult; Dev, deviance; Ju, juvenile; Nn, neonate; Par, number of parameters.

## The quasi-experimental context

Historically, the forest has been exploited for timber under a system of parcels or plots. At the end of 1999, very severe storms followed by the forest's classification as an integral biological reserve (1-a IUCN category) in 2006 brought logging to a sudden and definitive halt. We exploited the quasi-experimental situation created by the fortuitous combination of these drastic changes and the long-term snake surveys. Demographic parameters could be robustly estimated several years before and more than 20 years after the pivotal change in forest management. This total duration was long enough to allow the canopy closure processes to take place and to

trigger clear demographic responses. As the exchange of individuals between plot categories was negligible, the analyses were straightforward. It was thus possible to compare the populations living in plots that remained open with others that remained closed or closed rapidly.

## Influence of canopy closure on snake survival

Results suggest that in the most thermophilic species (*H. viridiflavus*), strong canopy closure was highly detrimental to the survival of neonates. When the canopy covered more than 70% of the surface area of the plots
<table><caption>TABLE 3 Estimated parameters for *Hierophis viridiflavus*, CIs, and SE, derived from the best multistate mark-recapture model C7_IS3_T2_S6.</caption><thead><tr><th>Main steps</th><th>Estimate</th><th>LCI</th><th>UCI</th><th>SE</th><th>Season</th><th>Age</th><th>Habitat</th></tr></thead><tbody><tr><td rowspan="4">C</td><td>0.004</td><td>0.001</td><td>0.026</td><td>0.004</td><td>Autumn</td><td>Nn and Ju</td><td></td></tr><tr><td>0.050</td><td>0.039</td><td>0.065</td><td>0.007</td><td>Autumn</td><td>Ad</td><td></td></tr><tr><td>0.091</td><td>0.055</td><td>0.147</td><td>0.023</td><td>Spring</td><td>Nn and Ju</td><td></td></tr><tr><td>0.399</td><td>0.355</td><td>0.445</td><td>0.023</td><td>Spring</td><td>Ad</td><td></td></tr><tr><td rowspan="10">IS</td><td>0.200</td><td>0.164</td><td>0.242</td><td>0.020</td><td></td><td>Nn</td><td>O-O</td></tr><tr><td>0.395</td><td>0.349</td><td>0.444</td><td>0.024</td><td></td><td>Ju</td><td>O-O</td></tr><tr><td>0.405</td><td>0.358</td><td>0.453</td><td>0.024</td><td></td><td>Ad</td><td>O-O</td></tr><tr><td>0.432</td><td>0.333</td><td>0.537</td><td>0.053</td><td></td><td>Nn</td><td>C-C</td></tr><tr><td>0.284</td><td>0.200</td><td>0.387</td><td>0.048</td><td></td><td>Ju</td><td>C-C</td></tr><tr><td>0.284</td><td>0.200</td><td>0.387</td><td>0.048</td><td></td><td>Ad</td><td>C-C</td></tr><tr><td>0.143</td><td>0.115</td><td>0.176</td><td>0.016</td><td></td><td>Nn</td><td>O-C</td></tr><tr><td>0.196</td><td>0.164</td><td>0.233</td><td>0.018</td><td></td><td>Ju</td><td>O-C</td></tr><tr><td>0.661</td><td>0.618</td><td>0.701</td><td>0.021</td><td></td><td>Ad</td><td>O-C</td></tr><tr><td rowspan="3">T</td><td>0.355</td><td>0.149</td><td>0.633</td><td>0.133</td><td></td><td>Nn to Ju</td><td></td></tr><tr><td>0.000</td><td>0.000</td><td>0.000</td><td>0.000</td><td></td><td>Nn to Ad</td><td></td></tr><tr><td>0.278</td><td>0.211</td><td>0.356</td><td>0.037</td><td></td><td>Ju to Ad</td><td></td></tr><tr><td rowspan="6">S</td><td>0.598</td><td>0.347</td><td>0.807</td><td>0.126</td><td></td><td>Nn</td><td>O-O</td></tr><tr><td>0.836</td><td>0.814</td><td>0.856</td><td>0.011</td><td></td><td>Ju and Ad</td><td>O-O</td></tr><tr><td>0.000</td><td>0.000</td><td>0.000</td><td>0.000</td><td></td><td>Nn</td><td>C-C</td></tr><tr><td>0.727</td><td>0.631</td><td>0.805</td><td>0.045</td><td></td><td>Ju and Ad</td><td>C-C</td></tr><tr><td>0.589</td><td>0.293</td><td>0.832</td><td>0.153</td><td></td><td>Nn</td><td>O-C</td></tr><tr><td>0.804</td><td>0.782</td><td>0.825</td><td>0.011</td><td></td><td>Ju and Ad</td><td>O-C</td></tr></tbody></table>

Note: Empty cells indicate no effect. Spring and autumn stand for spring-summer and autumn-winter seasons, respectively. Habitat stands for the three habitat categories.

Abbreviations: Ad, adult; C, recapture probability; IS, initial state; Ju, juvenile; LCI, lower CI; Nn, neonate; S, 5 months survival; T, transition; UCI, upper CI.

(C-C habitat), no neonate seemed able to survive or settle (neonates captured in C-C habitat were never recaptured; survival was null). The survival of juveniles and adults was also degraded in C-C and O-C habitats compared to O-O habitat, but less drastically. In the more thermo-conforming species (*Z. longissimus*), the influence of forest closure did not appear to affect survival in any age class. However, the significant and positive linear temporal trend found in O-O plots probably underlined the importance of open habitats (O-O) for maintaining healthy populations of *Z. longissimus* in a temperate forest undergoing rapid closure.

## The singular ecology of snake neonates

A very important methodological point is that we have distinguished the class of neonates as ecologically naïve individuals from that of juveniles that have settled into

their environment and have generally grown for a few years before reaching maturity. If we had put these two classes together in a single category (often named “juveniles” or “immatures” in the literature) as in the majority of studies (reviewed in King et al., 2018), we would not have been able to identify the differential effects of habitat changes on age-specific survival. Indeed, a model combining juvenile and neonate age classes was unable to detect the strong negative impact of the C-C habitat on survival for *H. viridiflavus* (model C7_IS3_T2_S3 with Nn and Ju combined, while keeping all groups; Table 2). Importantly, because we studied snakes throughout the entire active season, we were able to separate the true ecological neonates (i.e., naïve individuals that have been active for less than five months after birth [hibernation discounted]) from the small snakes of the year that we recaptured after their first spring (shortly after hibernation if they had grown or more than five months after birth if they had not grown). This later group includes
<figure><img src="image_3.png" /><figcaption>**FIGURE 1** Five-month survival estimates (±SE) in *Hierophis viridiflavus* and *Zamenis longissimus* according to age and forest plot categories. SEs are not visible in some cases (narrow SEs; see Tables 3 and 5). Ad, adults; C-C, Closed-Closed; Juv, juveniles; O-C, Open-Closed; O-O, Open-Open.</figcaption></figure>

small snakes that strongly resemble neonates (e.g., identi-
cal typical dorsal coloration), but that have survived
beyond the first five months and have therefore fed and
acquired key knowledge of their habitat. Note that, due
to cool conditions, snakes are rarely active before hiber-
nation in October and shortly after hibernation in April
and early May. Therefore, less than five months should
be taken into account. The importance of the first few
months for the establishment of neonate snakes in their
population has been demonstrated in a rattlesnake spe-
cies (Howze et al., 2012). Using an annual time step, as is
the case in most studies (i.e., considering that neonates
are yearlings by definition; e.g., Miller et al., 2011; or by
assigning juvenile status immediately after hibernation,

with the change of calendar year), would lack precision
to detect the mechanism that we have highlighted. Very
few demographic studies clearly distinguish between neo-
nates and juveniles (Lind et al., 2005).

The annual survival rate estimated in juveniles and
adults of *H. viridiflavus* and *Z. longissimus* (Appendix S1:
Table S4) falls within the range of values documented for
various snake species, typically 0.55–0.75 (King et al.,
2018). These relatively consistently high values (only 5 of
73 values were below 0.4 in tab. 2 in King et al., 2018)
contrast with the highly variable and sometimes very low
values found in naïve *H. viridiflavus* neonates, which
may reflect the sensitivity of this particular age class to
the ability to settle in a completely new environment.

Survival of *H. viridiflavus* neonates in
C–C plot

Survival estimates for *H. viridiflavus* neonates suggest that none survived in C–C plots. As all parameters were estimated (all models were full rank) and no neonates were recaptured in C–C plots during the study years, we are confident that this parameter can be interpreted biologically. The survival of neonates did not show a gradual decline as a function of plot categories, since it was similar for the O–O and O–C plots, close to 0.59 (Table 3).

The zero survival of *H. viridiflavus* neonates in the most closed habitat, and only there, could well be due to the virtual absence of their main prey, namely young wall lizards (*Podarcis muralis*) and green lizards (*Lacerta bilineata*) (Capizzi et al., 2008; Lelièvre et al., 2012; Luiselli et al., 2012). Neonate *H. viridiflavus* have low body reserves when hatchling (X. Bonnet, unpublished), so it is vital for them to find prey during the first few months of their active life. Very small lizards are a key food resource for neonate *H. viridiflavus* (easy to swallow and very attractive to these active sight-hunters). Monitoring of the two species of lizard in the Chizé forest shows that their presence depends on the persistence of open, sunny areas rich in bushes (O. Lourdais, personal communication). The sun's rays are essential for the herbaceous and shrubby stratum, which is home to rich communities of arthropods that support lizard populations and, in turn, snakes that feed exclusively or partially on them (Todd & Andrews, 2008). Wall and green lizards are highly thermophilic, especially small (presumably young) individuals that select warm thermo-regulation spots and seek out dense scrub (Capula et al., 1993; Gassert et al., 2013; Meek, 2014; Meek & Luiselli, 2022; Rugiero et al., 2021). In addition, these lizards are mainly insectivorous, with the youngest green lizards consuming mainly thermophilic arthropods such
<table><caption>TABLE 4 Modeling the effects of sex, habitat, and state (i.e., age classes) on demographic parameters for *Zamenis longissimus* in the Chizé forest between 1995 and 2021.</caption><thead><tr><th>Main steps</th><th>Model</th><th>Season</th><th>Period</th><th>Nn</th><th>Ju</th><th>Ad</th><th>Habitat</th><th>Sex</th><th>Par</th><th>Dev</th><th>AIC<sub>c</sub></th></tr></thead><tbody><tr><td rowspan="10">C</td><td>C1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>102</td><td>7432.65</td><td>7646.50</td></tr><tr><td>C2</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>66</td><td>8101.42</td><td>8237.49</td></tr><tr><td>C3</td><td>1</td><td>0</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>84</td><td>7470.71</td><td>7645.35</td></tr><tr><td>C4</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>60</td><td>7516.63</td><td>7640.00</td></tr><tr><td>C5</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>72</td><td>7470.71</td><td>7619.57</td></tr><tr><td>C6</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>72</td><td>7516.63</td><td>7665.49</td></tr><tr><td>C7</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>52</td><td>7498.22</td><td>7604.75</td></tr><tr><td>C8</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>60</td><td>7484.80</td><td>7608.17</td></tr><tr><td>C9</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>56</td><td>7487.19</td><td>7602.12</td></tr><tr><td rowspan="4">IS</td><td>C9_IS1</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>1</td><td>56</td><td>7487.19</td><td>7602.12</td></tr><tr><td>C9_IS2</td><td></td><td></td><td></td><td></td><td></td><td>0</td><td>0</td><td>46</td><td>7658.85</td><td>7752.83</td></tr><tr><td>C9_IS3</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>0</td><td>50</td><td>7625.79</td><td>7728.13</td></tr><tr><td>C9_IS4</td><td></td><td></td><td></td><td></td><td></td><td>0</td><td>1</td><td>48</td><td>7535.42</td><td>7633.58</td></tr><tr><td rowspan="4">T</td><td>C9_IS1_T1</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>1</td><td>56</td><td>7487.19</td><td>7602.12</td></tr><tr><td>C9_IS1_T2</td><td></td><td></td><td></td><td></td><td></td><td>0</td><td>0</td><td>41</td><td>7500.59</td><td>7584.16</td></tr><tr><td>C9_IS1_T3</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>0</td><td>47</td><td>7492.05</td><td>7588.11</td></tr><tr><td>C9_IS1_T4</td><td></td><td></td><td></td><td></td><td></td><td>0</td><td>1</td><td>44</td><td>7498.30</td><td>7588.11</td></tr><tr><td rowspan="6">S</td><td>C9_IS1_T2_S1</td><td></td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>41</td><td>7500.59</td><td>7584.16</td></tr><tr><td>C9_IS1_T2_S2</td><td></td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>29</td><td>7564.15</td><td>7622.93</td></tr><tr><td>C9_IS1_T2_S3</td><td></td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>1</td><td>35</td><td>7558.37</td><td>7629.52</td></tr><tr><td>C9_IS1_T2_S4</td><td></td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>1</td><td>35</td><td>7509.35</td><td>7580.50</td></tr><tr><td>C9_IS1_T2_S5</td><td></td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>25</td><td>7522.19</td><td>7572.78</td></tr><tr><td>C9_IS1_T2_S6</td><td></td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>29</td><td>7513.81</td><td>7572.59</td></tr><tr><td></td><td>C9_IS1_T2_S7</td><td></td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>27</td><td>7520.92</td><td>7575.60</td></tr></tbody></table>

Note: See Table 2 for details.

Abbreviations: Ad, adult; AIC<sub>c</sub>, corrected Akaike information criterion; C, recapture probability; Dev, deviance; IS, initial state; Ju, juvenile; Nn, neonate; Par, number of parameters; S, 5 months survival; T, transition.

as orthopterans and spiders (Angelici et al., 1997). Consequently, in closed habitat, *H. viridiflavus* neonates were probably unable to find their main prey and did not survive, or emigrated, yet none was recaptured in the other plot categories. Further, it is quite possible that, in the absence of bushy open spots, *H. viridiflavus* neonates cannot bask safely in the sun to reach the body temperatures required for digestion, reinforcing the negative effect of low prey availability. Indeed, although the adults bask directly in the sun, the very vulnerable neonates prefer to thermoregulate in the shelter of warm bushes, a microhabitat that disappears when the forest closes. Thus, another, nonexclusive, alternative is that the absence of dense bushes and bare forest floor in closed forest habitats increases the exposition and vulnerability of neonates to predation by birds and mammals, notably wild boars (Ballouard et al., 2021; Bonnet et al., 1999;

Duchesne et al., 2022; Graitson et al., 2019). In any case, forest closure, which inevitably takes place over just a few decades (Table 1), decreases neonate survival. This is reflected by the only negative temporal trend in survival, detected as expected in O-C plots for whip snake neonates. Due to this very low neonate survival, recruitment becomes negligible in the most closed areas, where juveniles and adults vanished with some delay (decades), and abundance collapses (Billy et al., 2024) despite a maximal longevity of over 20 years for these snakes (Fornasiero et al., 2016).

How can we explain the presence of the three age classes of *H. viridiflavus* in C-C plots if the neonates cannot survive there? The presence of neonates in C-C plots could be the result of local emigration from more favorable areas situated nearby (O-C and O-O plots). Indeed, the very high road mortality rates observed immediately
<table><caption>TABLE 5 Estimated parameters for *Zamenis longissimus*, CIs, and SE, derived from the best multistate mark-recapture model C9_IS1_T2_S6.</caption><thead><tr><th>Main steps</th><th>Estimate</th><th>LCI</th><th>UCI</th><th>SE</th><th>Season</th><th>Age</th><th>Habitat</th><th>Sex</th></tr></thead><tbody><tr><td rowspan="7">C</td><td>0.104</td><td>0.069</td><td>0.154</td><td>0.021</td><td>Spring</td><td>Nn and Ju</td><td></td><td>F</td></tr><tr><td>0.273</td><td>0.229</td><td>0.322</td><td>0.024</td><td>Spring</td><td>Ad</td><td></td><td>F</td></tr><tr><td>0.032</td><td>0.017</td><td>0.059</td><td>0.010</td><td>Autumn</td><td>Nn and Ju</td><td></td><td>F</td></tr><tr><td>0.023</td><td>0.014</td><td>0.037</td><td>0.006</td><td>Autumn</td><td>Ad</td><td></td><td>F</td></tr><tr><td>0.195</td><td>0.130</td><td>0.283</td><td>0.039</td><td>Spring</td><td>Nn and Ju</td><td></td><td>M</td></tr><tr><td>0.350</td><td>0.312</td><td>0.390</td><td>0.020</td><td>Spring</td><td>Ad</td><td></td><td>M</td></tr><tr><td>0.012</td><td>0.003</td><td>0.047</td><td>0.008</td><td>Autumn</td><td>Nn and Ju</td><td></td><td>M</td></tr><tr><td>0.038</td><td>0.028</td><td>0.051</td><td>0.006</td><td>Autumn</td><td>Ad</td><td></td><td>M</td></tr><tr><td rowspan="20">IS</td><td>0.194</td><td>0.153</td><td>0.243</td><td>0.023</td><td></td><td>Nn</td><td>O-O</td><td>F</td></tr><tr><td>0.367</td><td>0.314</td><td>0.424</td><td>0.028</td><td></td><td>Ju</td><td>O-O</td><td>F</td></tr><tr><td>0.439</td><td>0.383</td><td>0.496</td><td>0.029</td><td></td><td>Ad</td><td>O-O</td><td>F</td></tr><tr><td>0.343</td><td>0.268</td><td>0.427</td><td>0.041</td><td></td><td>Nn</td><td>C-C</td><td>F</td></tr><tr><td>0.336</td><td>0.261</td><td>0.420</td><td>0.041</td><td></td><td>Ju</td><td>C-C</td><td>F</td></tr><tr><td>0.321</td><td>0.247</td><td>0.404</td><td>0.040</td><td></td><td>Ad</td><td>C-C</td><td>F</td></tr><tr><td>0.292</td><td>0.244</td><td>0.344</td><td>0.025</td><td></td><td>Nn</td><td>O-C</td><td>F</td></tr><tr><td>0.310</td><td>0.262</td><td>0.363</td><td>0.026</td><td></td><td>Ju</td><td>O-C</td><td>F</td></tr><tr><td>0.398</td><td>0.346</td><td>0.453</td><td>0.027</td><td></td><td>Ad</td><td>O-C</td><td>F</td></tr><tr><td>0.145</td><td>0.107</td><td>0.194</td><td>0.022</td><td></td><td>Nn</td><td>O-O</td><td>M</td></tr><tr><td>0.200</td><td>0.155</td><td>0.254</td><td>0.025</td><td></td><td>Ju</td><td>O-O</td><td>M</td></tr><tr><td>0.655</td><td>0.595</td><td>0.711</td><td>0.030</td><td></td><td>Ad</td><td>O-O</td><td>M</td></tr><tr><td>0.189</td><td>0.135</td><td>0.257</td><td>0.031</td><td></td><td>Nn</td><td>C-C</td><td>M</td></tr><tr><td>0.283</td><td>0.218</td><td>0.358</td><td>0.036</td><td></td><td>Ju</td><td>C-C</td><td>M</td></tr><tr><td>0.528</td><td>0.451</td><td>0.605</td><td>0.040</td><td></td><td>Ad</td><td>C-C</td><td>M</td></tr><tr><td>0.140</td><td>0.109</td><td>0.178</td><td>0.018</td><td></td><td>Nn</td><td>O-C</td><td>M</td></tr><tr><td>0.105</td><td>0.078</td><td>0.139</td><td>0.015</td><td></td><td>Ju</td><td>O-C</td><td>M</td></tr><tr><td>0.755</td><td>0.710</td><td>0.795</td><td>0.022</td><td></td><td>Ad</td><td>O-C</td><td>M</td></tr><tr><td rowspan="3">T</td><td>1.000</td><td>1.000</td><td>1.000</td><td>0.000</td><td></td><td>Nn to Ju</td><td></td><td></td></tr><tr><td>0.000</td><td>0.000</td><td>0.000</td><td>0.000</td><td></td><td>Nn to Ad</td><td></td><td></td></tr><tr><td>0.196</td><td>0.154</td><td>0.246</td><td>0.023</td><td></td><td>Ju to Ad</td><td></td><td></td></tr><tr><td rowspan="6">S</td><td>0.156</td><td>0.058</td><td>0.360</td><td>0.075</td><td></td><td>Nn</td><td>O-O</td><td></td></tr><tr><td>0.836</td><td>0.815</td><td>0.855</td><td>0.010</td><td></td><td>Ju and Ad</td><td>O-O</td><td></td></tr><tr><td>0.214</td><td>0.075</td><td>0.476</td><td>0.104</td><td></td><td>Nn</td><td>C-C</td><td></td></tr><tr><td>0.833</td><td>0.798</td><td>0.863</td><td>0.016</td><td></td><td>Ju and Ad</td><td>C-C</td><td></td></tr><tr><td>0.305</td><td>0.177</td><td>0.473</td><td>0.077</td><td></td><td>Nn</td><td>O-C</td><td></td></tr><tr><td>0.862</td><td>0.845</td><td>0.878</td><td>0.008</td><td></td><td>Ju and Ad</td><td>O-C</td><td></td></tr></tbody></table>

Note: See Table 3 for details.

Abbreviations: Ad, adult; C, recapture probability; IS, initial state; Ju, juvenile; LCI, lower CI; Nn, neonate; S, 5 months survival; T, transition; UCI, upper CI.

after the hatching period strongly suggest that the main dispersal phase takes place shortly after birth in the two snake species studied, particularly in *H. viridiflavus* (Bonnet et al., 1999, 2021); postnatal dispersal might be frequent in snakes (Dubey et al., 2008; Howze et al., 2012). Zero survival and the absence of emigration,

whether successful or not, from closed forest areas to more open forest areas indicate that neonates arriving or born in much closed areas were trapped there. Accordingly, in C-C plots the probability of a snake being a neonate at first capture was higher than that of it being a juvenile or an adult (Table 3): Naïve neonates
explored the environment at random while older and more experienced individuals were more likely to avoid going into unfavorable areas.

## Survival of *H. viridiflavus* juveniles and adults

Compared with naïve neonates, juveniles and adults were more likely to be established in their home range (we did not detect dispersal in these age groups) and had access to a wider range of prey (higher hunting skills, higher swallowing capacities with increasing body size; Vincent et al., 2006). Their diet includes small mammals, birds, and other reptiles of all age classes and sizes. Their familiarity with their environment and their body size limit the range of potential predators. Large snakes are capable of greater routine movements than small individuals and have more extensive home ranges that may partly overlap with forest patches of different categories, possibly mitigating the negative effect of canopy closure (Hyslop et al., 2014). All these reasons may explain the higher survival rate in juvenile and adult *H. viridiflavus* monitored in closed plots. However, their abundance was much lower in C-C plots than in the other two O-C and O-O categories (Billy et al., 2024), while their survival tended to be higher in O-O plots (Figure 1). Overall, C-C plots appear very unfavorable for the whip snake.

## Survival of *Z. longissimus*

The diet of neonates is less restrictive in Aesculapian snake than in whip snake; small lizards are not a key resource for them (Lelièvre et al., 2012). The neonates, which feed mainly on the same species of small mammals as the juveniles and adults, capture very young voles, field mice, or shrews still in their nests. Although these small mammals (e.g., *Apodemus sylvaticus*) prefer forest edges, they can use a wide variety of forest habitats including arboreal strata (e.g., to feed on fruits) and they were represented in all plot categories (Rosalino et al., 2011; X. Bonnet unpublished data). Therefore, neonates should not excessively suffer from the absence of a particular species in a particular habitat. However, neonates should be conditioned by the birth cycles of small mammals (Rosário & Mathias, 2004), possibly creating fasting periods for the small snakes, which could partly explain the relatively low survival rate in this age class in all the forest plot categories. Because juveniles and adult *Z. longissimus* can eat larger prey than neonates (Arnold, 1993; Shine, 1991), their diet includes small mammals of all size classes, as well as birds (e.g., tits)

captured in the shrub and tree strata. This wider range of prey size may result in higher survival. *Z. longissimus* is a more discreet and cryptic species than *H. viridiflavus*, so it may suffer less from over-predation due to the disappearance of the herbaceous and bushy strata.

## Detrimental canopy closure for both species?

The results clearly showed that habitat closure following the classification of the forest as a biological integral reserve led to the decline of the most thermophilic species, *H. viridiflavus*. The small populations that persist in the two small open enclaves (O-O) of the forest are residual, isolated, and vulnerable. The once prosperous snake populations in the O-C plots are in steep decline and will probably be in near-extinction once the canopy is fully formed in less than a decade. The situation is less critical for *Z. longissimus*, as it is less dependent on open environments; it has lower metabolic requirements than *H. viridiflavus* and is therefore less dependent on access to sunlight (Lelièvre et al., 2010). It probably explains why both the survival of juveniles/adults, and abundance estimates were not strongly influenced by habitat categories. However, while open or semi-open habitats that are subject to closure are suitable for this species, their changes toward total closure (i.e., 100% canopy cover) are likely to pose acute problems.

In C-C plots, the canopy is evolving toward total closure and high-timber forest will dominate. At this stage, the forest floor is nearly bare, with the few bushes remaining scattered far apart (Billy et al., 2024). Aesculapian snakes, which spend much of their time at ground level, will be deprived of refuges and will be more vulnerable to predators (Lelièvre et al., 2011). This process of increasing forest closure will extend to the O-C plots. It is very likely that over the next few decades, *Z. longissimus* populations will in turn experience a decline. The decline of these two snake species in the foreseeable future, due to a lack of appropriate forest management, will deprive ecosystems of two predators which will have a negative cascading effect on ecosystem resilience (Adams et al., 2024). This goes against one of the major objectives of protected areas (Rodrigues & Cazalis, 2020).

## Management implications and conclusion

Managed temperate forests contain more protected plant species and greater biodiversity than uncultivated ones (Buckley, 2020; Duelli, 1997; Košulič et al., 2016;
Schulze, 2018; Sebek et al., 2015), and should be prioritized in biodiversity conservation efforts. More generally, the landscape's heterogeneity, specifically, the mosaic of open areas and small forest plots that is the result of habitat management, is crucial to maintaining biodiversity (Erdős et al., 2018). Therefore, in temperate deciduous forests, it would be wise to maintain rotating plots to create habitat mosaics (e.g., plots free to evolve, old-growth stands, coppices, and meadows). At a minimum, corridors of open areas should be created and maintained, such as along forest roads connected to forest edges.

In France, the rapid expansion of intensive agriculture and urbanization is reducing and fragmenting the habitats of reptiles. Forests could serve as refuges. Considering that reptiles are among the most endangered vertebrates (Cox et al., 2022) and considering that snakes are declining in large homogeneous and closed forest patches, it would be appropriate to implement minimal active conservation management in strictly protected areas such as the Chizé forest. A few percent of the forest area would be sufficient to promote populations (Bonnet et al., 2016). Such conservation management options are not considered, at least in France, where only the total area placed under strict protection status is considered a target to be achieved. By 2030, the European Commission plans to classify at least a third of protected areas as strict biological reserves (Arneth et al., 2023; Chape et al., 2005; Fuller et al., 2010; Hermoso et al., 2022). The expected benefits of this fundamentalist approach are not well supported by field studies. The current study, which concerns two species of meso-predators considered to be good indicators of biodiversity, shows that it is essential to change the rigid paradigm of forest management to adapt it to greater scientific reality (Beaupre & Douglas, 2009; Lewandowski et al., 2010; Oettel & Lapin, 2021). To achieve biodiversity objectives, the maximum level of protection for temperate forests should not be systematically regarded as a panacea (Bricca et al., 2024; Oettel & Lapin, 2021; Reczyńska et al., 2022).

## AUTHOR CONTRIBUTIONS

X. Bonnet initiated and managed long-term snake surveys. X. Bonnet and G. Billy conceived this study, collected, and handled the data. G. Billy, C. Barbraud, and X. Bonnet performed demographic analyses. X. Bonnet and G. Billy wrote the first draft. All authors contributed to writing, editing, and approved the final version.

## ACKNOWLEDGMENTS

We warmly thank G. Fosseries, J. M. Ballouard, and the many students who contributed to data collection. We also warmly thank A. Dasnon for her help with Esurge.

We are grateful to the Office National des Forêts for permission to work in the Chizé forest and to G. Naulleau who pioneered snake studies at the Centre d'Etude Biologique de Chizé. We are also grateful to one referee, R. Goldingay, who provided many valuable comments to improve the manuscript.

## CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

## DATA AVAILABILITY STATEMENT

Data (Billy et al., 2025) are available from Figshare: https://doi.org/10.6084/m9.f figshare.29851133.

## ORCID

C. Barbraud https://orcid.org/0000-0003-0146-212X

X. Bonnet https://orcid.org/0000-0001-6150-8199

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## SUPPORTING INFORMATION

Additional supporting information can be found online in the Supporting Information section at the end of this article.

**How to cite this article:** Billy, G., C. Barbraud, and X. Bonnet. 2025. "Contrasted Effects of Temperate Forest Closure on Snake Demography." *Ecosphere* 16(12): e70468. https://doi.org/10.1002/ecs2.70468