Jean François Julien

Christian Kerbiriou
email: kerbiriou@mnhn.fr

Marion Parisot-Laprun

Potential of restoration of gravel-sand pits for Bats

Keywords: gravel-sand pit, restoration of quarries, bat activity, bat community, wetland creation

Potential of restoration of gravel-sand pits for bats

Christian Kerbiriou, Marion Parisot-Laprun,

Introduction

Mining activities (steel industries, coal mining, rock or gravel sand extraction) have affected about 1 % of the land worldwide [START_REF] Walker | Ecosystems of disturbed land[END_REF]). These post-industrial sites represent an increasing component of many landscapes and regions (Tropeck et al. 2010) and there is currently an urgent need to solve problems related to ecological restoration of affected regions (Šálek 2012). After closing, most of these mining sites and quarries became neglected due to their decrease in economic value [START_REF] Dekoninck | Forest succession endangers the special ant fauna of abandoned quarries along the river Meuse (Wallonia, Belgium)[END_REF]. The original ecosystems have been removed, the original topography has been significantly changed and the previous ecological function has been irreversibly disrupted [START_REF] Milgrom | Environmental aspects of rehabilitating abandoned quarries: Israel as a case study[END_REF]. Spontaneous succession in those abandoned quarries resulted in a biodiversity pool that is significantly different from the original and surrounding habitats due to the dissimilarity between the physical and chemical substrate properties of the original and new soils [START_REF] Dekoninck | Forest succession endangers the special ant fauna of abandoned quarries along the river Meuse (Wallonia, Belgium)[END_REF][START_REF] Tischew | Implementation of basic studies in the ecological restoration of surface-mined land[END_REF]. However, the opinion on these post-mining sites has changed among conservationists as natural recovery occurring in these sites may sometime result in the creation of biodiversity refuges, particularly in human-exploited regions (Tropeck et al. 2010). Quarries are periodically disturbed and offer early successional stage, with extreme abiotic conditions leading to xerophilous open or oligotrophic habitats [START_REF] Krauss | Habitat area but not habitat age determines wild bee richness in limestone quarries[END_REF]Novak & Prach 2003). However similar conditions have become rare in human-exploited regions, because agriculture intensification processes contribute to increase the use of fertilizers, that in turn lead to eutrophication of soil and water and indirectly contribute to abandonment of marginal unproductive lands. This, in turn, promotes middle phase of succession, which is also favored by intensive forestry (i.e. fuelwood and shortening of cycle [START_REF] Bouget | Effects of fuelwood harvesting on biodiversitya review focused on the situation in Europe[END_REF]). In addition, many human actions induce control of natural perturbations (i.e. channeling of rivers, fire regime…etc.) in such a way that specialized species dependent on early successional stage and sparsely vegetated habitats are among the most threatened in many regions [START_REF] Morris | Re-creation of Early-successional Stages for Threatened Butterflies-an Ecological Engineering Approach[END_REF][START_REF] Hoekstra | Confronting a biome crisis: global disparities of habitat loss and protection[END_REF][START_REF] Wenzel | The severe decline of butterflies on western German calcareous grasslands during the last 30 years: a conservation problem[END_REF]. Literature is, therefore, quite abundant on the conservation potential of quarry sites for vascular plants [START_REF] Bizoux | Ecology and conservation of Belgian populations of Viola calaminaria, a metallophyte with a restricted geographic distribution[END_REF][START_REF] Shu | Natural colonisation of plants on five lead/zinc mine tailings in Southern China[END_REF]Tropeck et al. 2010;[START_REF] Wheater | The flora and invertebrate fauna of abandoned limestone quarries in Derbyshire[END_REF], spiders [START_REF] Tropek | Can quarries supplement rare xeric habitats in a piedmont region? Spiders of the Blansky les Mts[END_REF]Tropeck et al. 2010), odonata [START_REF] Harabis | High diversity of odonates in post-mining areas: Meta-analysis uncovers potential pitfalls associated with the formation and management of valuable habitats[END_REF][START_REF] Tichanek | Conservation value of post-mining headwaters: drainage channels at a lignite spoil heap harbour threatened stream dragonflies[END_REF], orthoptera (Tropeck et al. 2010), coleoptera [START_REF] Brändle | Diversity of surface dwelling beetle assemblages in open-cast lignite mines in Central Germany[END_REF], butterflies (Benes et al. 2003;Tropeck et al. 2010), wild bees [START_REF] Krauss | Habitat area but not habitat age determines wild bee richness in limestone quarries[END_REF], ants [START_REF] Dekoninck | Forest succession endangers the special ant fauna of abandoned quarries along the river Meuse (Wallonia, Belgium)[END_REF], amphibians [START_REF] Dolezalova | Technical reclamation and spontaneous succession produce different water habitats: A case study from Czech post-mining sites[END_REF][START_REF] Vojar | Spontaneous succession on spoil banks supports amphibian diversity and abundance[END_REF]) and birds (Šálek 2012). In addition to conservation policies focused on creating protected areas, it is increasingly argued that restoration of degraded areas must be undertaken in order to achieve worldwide ambitious targets (Aichi Biodiversity Targets) such as bringing close to zero the rate of loss of natural habitats. Based on the potential conservation value of these post-industrial sites, restoration management of quarries is now one of the major tasks in global restoration ecology [START_REF] Tischew | Implementation of basic studies in the ecological restoration of surface-mined land[END_REF]. One particularly important issue is the quantification of the roles of the various intrinsic, environmental and management factors on restoration success. In this context, several studies focus on the benefits of active restoration achieved by human intervention through reclamation works versus passive restoration where environmental stressors are removed and secondary succession takes place naturally. (see [START_REF] Brändle | Diversity of surface dwelling beetle assemblages in open-cast lignite mines in Central Germany[END_REF][START_REF] Prach | Ecological restoration of central european mining sites: a summary of a multi-site analysis[END_REF][START_REF] Šálek | Spontaneous succession on opencast mining sites: implications for bird biodiversity[END_REF][START_REF] Tropek | Can quarries supplement rare xeric habitats in a piedmont region? Spiders of the Blansky les Mts[END_REF].

Proper evaluation of restoration success requires first a standardized definition of success, though. Despite this pressing need, there still are no general and broadly accepted success criteria for restoration of quarries. This stems from several reasons: (i) original ecosystems have often been totally removed and newly hydrographic, physical and chemical conditions are so different that biodiversity pool can hardly return to a state close to the initial one, (ii) ecosystems before gravel sand extraction are rarely described and pristine ecosystems references are not easy to identify in some countries with long history of human footprint, (iii) quarries under restoration process are in a very dynamic state, (iv) there are rarely clearly defined biodiversity targets for quarries in conservation policies-strategies (i.e. which state or taxa to reach and promote). Therefore, restoration attempts may set goals that are too idealistic or based on incorrect assumptions of the state before human impacts [START_REF] Nilsson | Restoring riverine landscapes: the challenge of identifying priorities, reference states, and techniques[END_REF]. Indeed, as expected, the majority of studies dealing with biodiversity restoration within quarries did not clearly identify a target to reach. In addition, strong feedbacks between biotic factors and the physical environment can alter the efficacy of restoration management [START_REF] Suding | Alternative states and positive feedbacks in restoration ecology[END_REF]). Studies indicates that some degraded systems are resilient to traditional restoration efforts owing to constraints such as drastic changes of biogeochemical processes, changes in landscape connectivity, loss of native species pools, shifts in species dominance, invasion by exotics [START_REF] Suding | Alternative states and positive feedbacks in restoration ecology[END_REF]). Here, we focus on gravel-sand pits, a type of mining activities, which impact the original topography. After end of operating such quarries are colonized by body of water due to the massive extraction of sand and gravel of old riverbed and the water table. While a return to the original topography is thus not an option, the target state identified is aquatic habitat. Such spaces are then dedicated for public recreation facilities or for nature conservation but never return to some original land uses such as agriculture land.

Moreover, the great majority of studies that monitored biodiversity along successional stages in quarries rarely used external standardized references to assess comparisons between the biodiversity present within quarries and other habitats (see [START_REF] Bonifazi | Monitoring of abandoned quarries by remote sensing and in situ surveying[END_REF][START_REF] Brändle | Diversity of surface dwelling beetle assemblages in open-cast lignite mines in Central Germany[END_REF][START_REF] Dekoninck | Forest succession endangers the special ant fauna of abandoned quarries along the river Meuse (Wallonia, Belgium)[END_REF][START_REF] Dolezalova | Technical reclamation and spontaneous succession produce different water habitats: A case study from Czech post-mining sites[END_REF][START_REF] Krauss | Habitat area but not habitat age determines wild bee richness in limestone quarries[END_REF][START_REF] Milgrom | Environmental aspects of rehabilitating abandoned quarries: Israel as a case study[END_REF][START_REF] Novák | Proximity of valuable habitats affects succession patterns in abandoned quarries[END_REF][START_REF] Novák | Artificial sowing of endangered dry grassland species into disused basalt quarries[END_REF][START_REF] Prach | Spontaneous vegetation succession at different central European mining sites: a comparison across seres[END_REF][START_REF] Tropek | Spontaneous succession in limestone quarries as an effective restoration tool for endangered arthropods and plants[END_REF][START_REF] Tichanek | Conservation value of post-mining headwaters: drainage channels at a lignite spoil heap harbour threatened stream dragonflies[END_REF][START_REF] Vojar | Spontaneous succession on spoil banks supports amphibian diversity and abundance[END_REF][START_REF] Yuan | Soil Formation and Vegetation Establishment on the Cliff Face of Abandoned Quarries in the Early Stages of Natural Colonization[END_REF][START_REF] Zhang | Plant Recruitment in Early Development Stages on Rehabilitated Quarries in Hong Kong[END_REF], for the few studies that used explicit external references see: Benes et al. 2003;[START_REF] Khater | Spontaneous vegetation dynamics and restoration prospects for limestone quarries in Lebanon[END_REF]Tropek & Konvicka 2008. External references (i.e. biodiversity states assessments on sites without quarry activity or outside of restoration process) usage allows, however, unbiased evaluation of the conservation value of quarries for biodiversity. What's more, it enables the definition of objective goals and thus impartial assessment of restoration success. In this way, we mobilize biodiversity data in quarries, using ROSELIERE scheme and we use independent dataset provide by VIGIE NATURE a national biodiversity monitoring scheme based on citizen science for provide an external reference. ROSELIERE (http://programmeroseliere.fr/node/21), is a biodiversity monitoring scheme focused on evaluating biodiversity dynamics in French gravel-sand pits, implemented since 2006. The main goals of the ROSELIERE program are (i) to assess the level of biodiversity in a large number of quarries nationwide (ii) assess the success of restoration programs of gravel-sand pits (iii) understand the basic processes that promote or reduce the conservation effectiveness of these restoration programs. ROSELIERE currently aims, thus, to monitor 12 taxonomic groups (birds, bats, amphibians, aquatic macro-invertebrates, butterfly, plants….) and is based on protocols consistent with national monitoring.

Measuring restoration at the community level is particularly tough, due to the great variability inherent in most natural communities and may require a focus on restoration of community function (e.g., trophic structure) rather than a focus on the restoration of a particular species (Palmer et al. 1977). Here we propose to focus on bat taxa, because this group and microchiropterans particularly are long live species and act as important biodiversity indicators as their population trends reflect those of lower trophic level species thus tracking the biodiversity response to anthropogenic pressures [START_REF] Jones | Carpenoctem: the importance of bats as bioindicators[END_REF].

Furthermore, several studies have highlighted their value in terms of providing ecosystem services [START_REF] Kunz | Ecosystem services provided by bats[END_REF], such as pest control [START_REF] Cleveland | Economic value of the pest control service provided by Brazilian free-tailed bats in south-central Texas[END_REF] seed dispersal [START_REF] Medellin | Seed Dispersal by Bats and Birds in Forest and Disturbed Habitats of Chiapas, Mexico1[END_REF]1999;[START_REF] Kelm | Effects of artificial roosts for frugivorous bats on seed dispersal in a neotropical forest pasture mosaic[END_REF] and pollination (Flemming et al., 2009). We measure bat activity using acoustic recorder, this metric based on bat echolocation is a diversity index, which directly include trophic function, because bats that hunt for flying insect, use echolocation to detect, identify, and localize prey [START_REF] Schnitzler | Echolocation by insect-eating bats[END_REF].

Indeed bat activity is used by academics researchers to investigate differential use of habitat by bats [START_REF] Sherwin | The efficacy of acoustic techniques to infer differential. Use of habitat by bats[END_REF]. Additionally, from a conservationist point of view, bats are a group of interest, because they are increasingly threatened worldwide [START_REF] Mickleburgh | A review of the global conservation status of bats[END_REF]. An important part of European bat species (40%) have a poor conservation status much of their range (Barova & streit 2014) because of various pressures, such as the loss of suitable foraging habitats [START_REF] Walsh | Foraging habitat preference of vespertilionid bats in Britain[END_REF], agricultural practices that use toxic pesticides [START_REF] Swanepoel | Energetic effects of sublethal exposure to lindane on pipistrelle bats (Pipistrellus pipistrellus)[END_REF][START_REF] Wickramasinghe | Abundance and species richness of nocturnal insects on organic and conventional farms: effects of agricultural intensification on bat foraging[END_REF]), emerging infectious diseases [START_REF] Frick | An Emerging Disease Causes Regional Population Collapse of a Common North American Bat Species[END_REF], urbanisation [START_REF] Loeb | Relationship between urbanization and bat community structure in national parks of the southeastern U[END_REF], forest management (O'Donnell 2000) and roost destruction and disturbance [START_REF] Mitchell-Jones | Protecting and managing underground sites for bats[END_REF]. In response to these pressures, answers in terms of protection have been implemented: all Europeans bats are legally protected in European countries through national or European laws (Council Directive 1992, Convention on Migratory Species (CMS 1985(CMS -2008)), and Agreement on the conservation of Populations of European Bats). In addition to species protection, 31% of European bat species are target species for the designation of Natura 2000 conservation areas (Barova & streit 2014). To our knowledge, however, and despite this established role as valuable indicator, this particular group has never been studied in the context of quarry restoration.

Considering that relative abundance, diversity or success of restoration are relative states, we compared bat activity measures on gravel-sand pits sites (before operating, during quarrying or in rehabilitated sites) to bat activity measures on the main habitats present in France using data provided by VIGIE NATURE (http://vigienature.mnhn.fr/) and its dedicated survey of bat population (the French Bat Monitoring Program, FBMP). We paid close attention to comparison between gravel-sand pits states and aquatic habitats, because the restoration process in the gravel-sand pits studied often leads to bodies of water and these habitats are among the most favorable for numerous bats species. We also focus comparisons between gravel-sand pits states and arable land because newly gravel-sand pit settlements are usually planned on such agricultural land. Finally, we hypothesize that bat activity and mean communities diversity index based on bat activity will increase with timespan after beginning of rehabilitation.

Methods

Study Area

The study was conducted in 21 gravel-sand pits. A significant portion of sites (n=19) is comprised from the original launch area of the ROSELIERE program: the Bassée, an alluvial plain of the Seine located 90km south east from Paris, France. Two other sites were added to the network, all in the Atlantic and Continental biogeographical area (Figure 1). After decommission, the rehabilitation mainly leads to an ecological vocation with facilities favorable to the wildlife. These gravel-sand pits mainly evolved from bare soil (73% of sites sampled during quarrying) to bodies of water (due to the natural rise of the water table resulting from the sand extraction, 47% of sampled points >10 years after operating). At the level of the gravel-sand pit, the surface of the piece of water, representing an average of 42 % of the total pit area. A spontaneous succession process occurs, leading to the installation of an afforestation on terrestrial areas (15% of sampled points >10 years after operating). Some sites also include meadows being managed by grazing or mowing. Our sampled points in gravel-sand pits included a variety of vegetation types, we believe it provides a detailed picture of the current existing gravel-sand pits states, with its known bias toward more bushy and wooded vegetation for gravel-sand pits sampled long time after operating (see Appendix A). According to the type of quarries studied (gravel-sand pits in alluvial context), sampled points were often very close to aquatic habitats (mean average distance to water 202m±68 (SE). In addition to these gravel-sand pit sites, we selected external data from 76 sites of the French Bat Monitoring Program (FBMP; [START_REF] Kerbiriou | Long term trends monitoring of bats, from biodiversity indicator production to species specialization assessment[END_REF]) located in the same biogeographical area (Figure 1) excluding Alpine region and the Mediterranean region, which host very different communities of bats (Dietz et al. 2009), with the aim of providing a measure of bat activity levels in gravel-sand pits (before and during quarrying or in rehabilitated sites) in comparison to a set of habitats reference. The FBMP sampling design consists of a randomly selected, 2km-sided, square, within which ten points are chosen by the observer. Such a sampling design resulted in a survey of habitats that are quite representative of those at the French scale (R²=0.95). One to five points were sampled in gravel-sand pit sites depending on the site size (mean: 4.4±0.3). Due to the type of studied quarries (gravelsand pit in an alluvial context), sampled points were often very close to aquatic habitats.

Whatever the site considered, points were spaced out by 200 meters and placed among the quarry's main habitats. A total of 93 efficient points were sampled in gravel-sand pits and 724 for the FBMP (Table 1)

Bat Sampling

Acoustic recording

We use bat activity measures, an approach widely used by researchers working for environmental consulting firms, government agencies (Adams et al. 2012, for example during evaluation of development projects) or academics researchers to investigate differential use of habitat by bats [START_REF] Russo | Use of foraging habitats by bats in a Mediterranean area determined by acoustic surveys: conservation implications[END_REF]Azam et al. 2016). Gravel-sand pits sites were sampled between 2009 and 2013 following a standardized echolocation recordings protocol similar to the one designed for the French Bat Monitoring Program (FMBP, 2012), from which we used data collected from 2006 to 2013.

For both ROSELIERE and FMBP programs, bat calls were detected using a Tranquility Transect Bat detector (Courtpan Design Ltd, UK) and recorded over 6 minutes. In each plot, echolocation recordings were carried out during two visits corresponding to bats activity peaks: first, during the 15 th June to 31 st July timespan, during which females are expected to give birth and feed their offspring; second, during the 15 th August to 30 st September timespan, during which youngs are flying. All points of any given site were sampled during the same night. The observers begin their sampling thirty minutes after dusk, in the same order for each visit (from season to season, and from year to year). Thus this sampling occurred during the bat activity peak that begins 30 minutes after sunset and spans less than 3 hours [START_REF] Roche | Development of a Car-Based Bat Monitoring Protocol for the Republic of Ireland[END_REF]. Observers sampled bats only when weather conditions were favourable (no rain, temperature higher than 12°C and wind speed less than 5 m/sec). For more details on protocol see Appendix A. The whole data set is composed by 711 records in gravel-sand pits and 2263 records from the FBMP.

Bats identification and bat activity measures

Species calls were identified using Syrinx software version 2.6 [START_REF] Burt | Syrinx a software for real time spectrographic recording, analysis and playback of sound[END_REF] for spectrogram analyses. For the ROSELIERE data, identifications were made by the authors.

For the national data, identifications were made by voluntary observers and then validated by Museum's scientists (CK, JFJ, Yves Bas). Identification was made at the species level except for two genera: Plecotus and Myotis, for more details on bats identification see Appendix B.

As it is impossible to distinguish individual bats from echolocation calls, we measured, on each sampled site, bat activity, defined as a mean number of bat pass per species (a bat pass corresponds to a trigger of the bat detector in time expansion). The response variables were (i) species abundance of foraging calls (n=7 taxa), (ii) the total abundance of foraging calls, (iii) species richness and (iv) Community Habitat specialization index (CSI). We calculated (CSI) as the arithmetic mean of the species habitat specialization index (SSI) of the detected species weighted by their abundance (see Appendix C for more details about the assessment of CSI and SSI). Note that the CSI and the total abundance of foraging calls are two metrics that could be potentially biased by an abundant specie.

Sampled points characteristics

Gravel-sand pit points were grouped into five categories (Table 1), according to the state of extraction or rehabilitation: before operating (B.O.), during quarrying (D.Q.) and three categories of rehabilitation according to the elapsed time after operating (<5 years; 5 years<<10 years and >10 years).

In order to assess the difference between gravel-sand pits and common habitats present in France, we collected habitat characteristics in a radius of 100m around the 724 points provided by the FBMP (Table 1), using a detailed hierarchical habitat classification [START_REF] Kerbiriou | Long term trends monitoring of bats, from biodiversity indicator production to species specialization assessment[END_REF] relatively similar to the one used for bird-habitat classification system [START_REF] Crick | A bird-habitat coding system for use in Britain and Ireland incorporating aspects of land-management and human activity[END_REF] and with the first classes consistent with Corine Land Cover classification.

Based on a minimum number of replicate per habitat category (n=24), we selected 17 habitat types (Table 1). Among these habitats, we paid a special attention to (i) bodies of water category (5.1.2, Corine Land Cover category) because they are the targeted state and (ii) cereal crops, (2.1.1, Corine Land Cover category) because newly gravel-sand pit settlements are usually planned on such agricultural land and furthermore because arable land represents the major land-use pressures for bats (Azam et al. 2016).

Data Analysis

Relative abundance of bat activity in gravel sand pit compared to the main habitats present in France

In a first assessment of gravel-sand pits as foraging/commuting habitats for bats, we compared bat activity (i.e. response variable) in the 93 sample points in gravel-sand pits (ROSELIERE) with 724 points from the FBMP database, respectively to each habitat. Bat activity is either species abundance, total abundance, richness and CSI.

We assessed potential differences in bat activity among habitats (i.e. common habitats for FBMP points and the five categories of uses for gravel-sand pits) using Generalized Mixed Models (GLMM; package GLMMADMB, Bolker 2015). The protocol is performed only when weather conditions are generally favourable, however, we took into account temperature as a co-variable because we assumed that bat activity might be affected by weather conditions [START_REF] Ciechanowski | Spatiotemporal variation in activity of bat species differing in hunting tactics: effects of weather moonlight, food abundance, and structural clutter[END_REF]). Because each visit covered two different periods of the bat life cycle and might have influenced bat activity we also included a season variable. In addition, as yearly changes in bat abundance can be expected, we included a year effect (year as a factorial variable). According to the hierarchical structure of our sampling design (same sites sampled year to year and several points within a same site), we treated the site variable as a random effect, while considering the other explanatory variables (season, temperature, year, habitats) as fixed effects [START_REF] Zuur | Mixed Effects Models and Extensions in Ecology with R. Statistics for Biology and Health[END_REF]). We did not included local vegetation characteristics in modelling because it is obviously correlated with time elapsed after operating (see Appendix A). In addition, we hypothesized that close points, even if their habitat differs, are likely to have a similar bat population density due to similar climatic conditions or large-scale landscape compositions. Thus, to account for spatial autocorrelation, Where bat activity could be bat specific abundance (n=8) or total abundance, richness and CSI. Habitat is a categorical variable with 22 categories (including 5 states of gravel-sand pit and the 17 main habitat present in France see Table 1).

Due to the nature of the response variable (bat count) and potential over dispersion we performed, for each species, GLMMs with a Poisson error distribution, a negative binomial distribution and zero inflation models with a negative binomial or Poisson error distribution [START_REF] Zuur | Mixed Effects Models and Extensions in Ecology with R. Statistics for Biology and Health[END_REF]. Choice and validation of model were based on a multi-criteria approach following [START_REF] Zuur | Mixed Effects Models and Extensions in Ecology with R. Statistics for Biology and Health[END_REF] looking at potential pattern in residual and AIC value and pseudo R-square. When the model did not fit well, we transformed the response variable (i.e. bat activity abundance) in a presence/absence variable and then used a binomial error distribution.

Models selected are shown in Appendix D. Finally, in order to test pairwise comparisons between habitats (and particularly bodies of water, the habitat reference), we ran a Tukey post hoc tests (package lsmeans, Lenth R. 2015).

Variation of bat activity across gravel sand pit life's cycle

Using similar modelling approaches (GLMMs with negative binomial error distribution), as previously, we focused our analysis on variation of the global effect, independently of the considered species, between the five gravel-sand pit states (before operating, during quarrying and three rehabilitation categories depending on the elapsed time after the quarry stopped operating). Thus, we added species identity as a random effect to account for differences in abundance between species [START_REF] Jiguet | Bird population trends are linearly affected by climate change along species thermal ranges[END_REF][START_REF] Pavón-Jordán | Effects of flyway-wide weather conditions and breeding habitat on the breeding abundance of migratory boreal waterbirds[END_REF][START_REF] Pellissier | Assessing the Natura 2000 network with a common breeding birds survey[END_REF]. Our statistical models were structured in the following way:

[Bat activity] ~ gravel-sand pits state + season + temperature + year + autocovariate + 1|Site +1|species Where bat activity is bat specific abundance.

Effects of each variable were evaluated using a type II ANOVA with an F-test.

Results

Species contacted

The FBMP network (n =724 sites) yielded 12385 contacts for 17 bats taxa while ROSELIERE network of gravel-sand pits (n=93 sites) yielded 1698 contacts for 12 bats taxa. The taxa which occurred sufficiently to allow assessing bat activity at the level of the 22 habitat classes (i.e. the 5 gravel-sand pit states and the 17 habitat classes from FBMP) where were: P. pipistrellus (59%), P. kuhlii (8%), P. nathusii (4%), N. noctula (6%), N. leisleri (8%), E. serotinus (5%) and Myotis ssp (10%), details of species occurrence per habitats are provided in Appendix E.

Relative abundance of bat activity in gravel-sand pits compared to France wide representative habitats

As expected, bat activity varied among habitats and between species (Fig. 2,). While the average of bat activity appeared globally lower in gravel-sand pit states than in bodies of water (i.e. the reference habitat) for most species, we did detect relatively few significant differences, mainly due to great variance around estimate (see Fig. 2 and Appendix F). The notably significant differences (Tukey post hoc tests with a significance level alpha = 0.05, see Appendix F) in bat activity were detected for P. pipistrellus and Myotis ssp, for which richness and total of abundance of foraging calls activity were greater in bodies of water than in pre-operating sites. In addition, richness was greater in sites rehabilitated more than 10 years ago than before operating. Myotis ssp abundance on arable land were significantly lower than on gravel-sand pits rehabilitated more than 5 years ago. Similarly, P. nathusii and N. leisleri abundance in gravel-sand pits rehabilitated more than 10 years ago was also significantly greater than arable land.

Variation of bat activity across the gravel-sand pit life's cycle

When focusing on the global effect of gravel-sand pits states, regardless of the considered species, we showed that this variable influences significantly bat activity (Table 2). While bat activity appears increasing during the gravel-sand pit life's cycle (Fig. 3), only gravel-sandpits which rehabilitation is older than 10 years display bat activity greater than the four other gravel-sand pit states (Tukey post hoc tests with a significance level alpha = 0.05). This result is not qualitatively influenced by P. pipistrellus (i.e. the most abundant species) see Appendix G.

Discussion

Bats in gravel-sand pits

This study shows that several bats inhabit gravel-sand pit sites, regardless of the quarrying life cycle, in particular, even during quarrying extraction. P. pipistrellus is clearly the species exhibiting far from the other a high level of activity, this pattern is a constant among studies dealing with bat activities in Northern and Western Europe (Wickramasinghe et al. 2003, Roche et al. 2011[START_REF] Newson | A novel citizen science approach for large-scale standardised monitoring of bat activity and distribution, evaluated in eastern England[END_REF]. However, contacted species are mainly relatively common species, while rare or threatened species (i.e. species listed on the Annexe II of the EU Habitats Directive (EEC 1992) or in the French IUCN red list) were almost never contacted. Only two contacts of a rare species (Myotis emarginatus) were recorded in two different gravel-sand pits which had been rehabilitated more than 10 years ago. The quasiabsence of rare or threatened species could be linked to (i) the nature of sampled sites: indeed, neither ROSELIERE or FBMP programs focused on remarkable sites such as reserves or pristine areas; (ii) ROSELIERE's main sampled region, Île-de-France, undergoes a lot of anthropogenic pressures and is not the most welcoming French region for biodiversity; (iii) the protocol used, which is based on short time recording (i.e. 6 minutes). This characteristic of the protocol was designed to allow observers to sample several sites during the same early night. With the recent arrival on the market of new generation of bat detector-recorder, we could consider recording throughout the entire night (see Azam et al. 2015;[START_REF] Stahlschmidt | Bats as bioindicatorsthe need of a standardized method for acoustic bat activity surveys[END_REF] and thus expect increasing the probability of contacting rare species. We will be able to utilize, in future studies, data from the recent third protocol of the FBMP (2012) which is based on such technology (Bas et al. 2015). In addition, we recommend in the future, when a quarry would be involve in a long term ecological survey to promote also the implantation of a FBMP sites survey close to this quarries site.

When looking at the average of bat activity in gravel-sand pit states (i.e. reflecting their interest in term of foraging areas), this parameter displays a range comparable to what is observed in numerous habitats but appears lower than in bodies of water (which could be considered as the target to reach), though appears greater than in arable land (i.e. the major land-use pressure and currently often the habitat type where gravel-sand pits are planned to be exploited). We did, however, detect relatively few significant differences due to great variance around estimate and low occurrence of some species. This great variance could be linked to (i) the short time recording of this protocol, (ii) the nature of the response variable, i.e. bat activity measure, which is naturally characterized by great variance (Barlow 2015), or (iii) differences between sites. This latest non-exclusive hypothesis should be explored to allow for identifying intrinsic or surrounding site characteristics that could explain lower or greater abundance for a similar gravel-sand pit life cycle category, then permitting the exploration of ways to maximize bat abundance.

Our findings concerning (i) the globally low levels of bat activity in pre-operating sites (Fig. 2) and (ii) the significantly lower bat activity for P. pipistrellus and Myotis ssp, richness and total abundance of foraging in pre-operating sites compared to what's observed in bodies of water (Table S5), indicate that sites chosen to develop extracting activity seem to globally follow the mitigation hierarchy to avoid and/or limit the negative effects of project development on biodiversity (e.g., avoid development in biodiversity hotspot, in areas where rare or threatened species occur (BBOP 2012;[START_REF] Fox | Status of species conservation banking in the United States[END_REF][START_REF] Regnery | Offset measures and development projects: the conservation of protected species under the EU Birds and Habitats Directives[END_REF])).

Variation of bat activity during the life cycle of quarrying

Bat activity appears increasing during the gravel-sand pit life's cycle (Fig. 3), but only gravelsand pits which had been rehabilitated for more than 10 years exhibited greater bat activity than observed in the four other gravel-sand pit states, highlighting the length of time required to detect obvious changes in the attractiveness of site being rehabilitated. A number of studies also highlight the positive influence of aged quarries on species richness, e.g. for birds (Šálek 2012) or terrestrial plants [START_REF] Prach | Ecological restoration of central european mining sites: a summary of a multi-site analysis[END_REF][START_REF] Prach | Spontaneous vegetation succession at different central European mining sites: a comparison across seres[END_REF], while other find a negative effect, for butterflies (Benes et al. 2003). [START_REF] Brändle | Diversity of surface dwelling beetle assemblages in open-cast lignite mines in Central Germany[END_REF] did not detect any age effect on dwelling beetle richness, neither did [START_REF] Krauss | Habitat area but not habitat age determines wild bee richness in limestone quarries[END_REF] on wild bees richness although they tested an age gradient of over 120 years, habitat areas being the best predictor. These contrasted findings among taxa are probably linked to their habitat requirement, bees and butterflies' communities are probably favored by open habitats such as grassland present in early stage of succession while birds and bats need more wooded habitats occurring in late succession. An overview of sites disturbed by mining in the past 50 years in Czech Republic [START_REF] Prach | Ecological restoration of central european mining sites: a summary of a multi-site analysis[END_REF] indicates that the time to more or less stabilized late vegetation usually occurred between 20 to 60 years (20 years for gravel-sand pits). In addition to spontaneous vegetation succession, the species colonization capacities and surrounding landscape must be taken into account. [START_REF] Flavenot | Impact of quarrying on genetic diversity: an approach across landscapes and over time[END_REF] find that genetic diversity of toads population in quarries could be linked to the surrounding habitat structure. This structure present 60 years ago was determinant for Bufo bufo, while the effect was significant only for the habitat structure present 10 years ago for Bufo calamita, which is considered to be more dispersive than B.

Bufo. It was also demonstrated that quarries can host pioneer habitat that promotes Bufo calamita.

Conservation implications

This study shows that (i) several bats inhabit gravel-sand pit sites, independently of the quarrying status, (ii) bat activity average on quarries has the same order of magnitude than in numerous habitats but appears to be lower in gravel-sand pit stages than in bodies of water (i.e. the habitat that could be identified as a target to reach), and (iii) time elapsed after quarry operations acts as a driver of bat activity. Thus this study highlights the conservation value of quarries as foraging areas for bats, but also the time delay required to detect significant increase in bat activity (>10years). In the framework of the mitigation hierarchy (BBOP 2012), the third step consists in conducting on-site or ex-situ restoration or rehabilitation to correct the negative impacts of the project. Time delay is then a key point: the greater the importance of time needed to recover, the more significant transient biodiversity losses will become. Such losses will likely result if human activity and its impacts are allowed to occur before offsetting measures are put in place. The most straightforward solution, however, is to require offsets to be effective before losses occur or as soon as possible after any impact is observed [START_REF] Quétier | No net loss of biodiversity or paper offsets? A critical review of the French no net loss policy[END_REF]). In the case of gravel-sand pits, the extraction site is often a mosaic of patches with different states and uses, and restoration begins immediately after the end of extraction on each patch. Therefore, disturbance is limited and species can colonize the area while another sector is exploited (principle of coordinated rehabilitation). As they generate new natural spaces (bodies of water or ponds, grasslands, shrubs and later woodlands…), rehabilitated areas offer hunting habitats for bats while extraction still occurs in the vicinity. Comparatively, the attractiveness of these areas is often all the more important that intensive agriculture was practiced on the site pre-extraction and that human pressure subsided and quiet is restored.

A possible solution to address the issue of conservation value that differs depending on taxa over the succession evolution (favorable in early stage for pioneers species or open habitat specialized species and favorable in late stage for species linked to more productive, mature habitat, or forest specialized species) could consist in clearly defining a target for a site (i.e. arbitrate the priority: which taxa should be favored according to the site stakes) and thus planning an adapted management. For example, if conservation of xerophilous butterflies is defined as the target to reach, preventing natural vegetation succession and planning to maintain or to restore patches of earlier-succession habitat could be enforced (Benes et al. 2003). Another solution would be to attempt to maintain a mosaic of different succession stages within sites, this solution could be more easily implemented when restoration is coordinated with extraction. This mosaic approach within site may depend on site size, indeed [START_REF] Krauss | Habitat area but not habitat age determines wild bee richness in limestone quarries[END_REF] underline that the major driver of bee richness was habitat area, this approach is thus probably not recommended for small sites.

A perspective in this research is now to identify the respective importance of intrinsic variables (i.e. vegetation structure, site size…etc.) and landscape variables (surrounding habitat, connectivity…etc.) that could increase the attractiveness of the sites. Île-de-France). We deeply thank the voluntary observers who took part in the French Bat Monitoring Program, a large-scale survey which relies entirely on them. Finally, we thank C.

Appendix

Laprun for an earlier reading of our manuscript

Legends of tables and figure

Table 1. number of sampled points per state of quarrying or habitat and in bracket the number of data when years replicate are taken into account.

Table 2. Results of the modelling of bat activity's variation across gravel-sand pit life's cycle.

  we added an autocovariate (i.e., a distance-weighted function of neighboring response values) with the autocov dist function in R (package spdep, Bivand R. et al. 2011). Thus our statistical models were structured in the following way: [Bat activity] ~ habitat + season + temperature + year + autocovariate + 1|Site

  Detailed information on the French Bat Monitoring Program, count point protocol (Appendix A), Bats identifications (Appendix B), Assessment of habitat specialization species index and community specializations indices (Appendix C), Model selection for modelling bat activity between habitats (Appendix D), Appendix E: Average occurrence and bat activity among the different gravel-sand pit state and habitat (Appendix E), Pairwise comparisons between habitats (Appendix F), Impact of taking into account or not P. pipistrellus (i.e. the most abundant species) on assessment of age of gravel-sand pits restoration effect on relative importance of bat activity (Appendix G) are available online,. Acknowledgement This work was co-funded by French National Union of Quarrying and Materials Industries of Île-de-France (UNICEM IDF), French National Union of Aggregate Producers (UNPG), operators on extracting sites (A2C Granulats, CEMEX, GSM, Lafarge Granulats, Sables de Brévannes) and a naturalist NGO (Association des Naturalistes de la Vallée du Loing et du massif de Fontainebleau, ANVL). The authors certify that the funding source had no influence on the collection, analysis or interpretation of the data. The authors have declared that no competing interests exist. This program could not have been possible without the motivation and involvement of C. Parisot, initiator of the ROSELIERE program. We thank naturalists NGO (ANN, Atelier des territoires, AVEN du Grand Voyeux, CDPNE, CREN Midi-Pyrennées, CSNHN, FDC Haute-Garonne, FRAPNA Loire, GONm, Loiret Nature Environnement, LPO Aquitaine, LPO Isère, LPO PACA, LPO Sarthe, NaturAgora, SEPANSO Gironde, SEPANSO Landes, Seine-et-Marne Environnement) and engineering offices (Alfa Conseil, Sciences Environnement) involved in data collection in gravel-sand pit sites, and owners of rehabilitated sites (Water Agency of Seine-Normandie, Agence des Espaces Verts of Île-de-France, Department of Seine-et-Marne, Eau de Paris and Pro Natura

Figure 1 .

 1 Figure 1. Map of the distribution in France of the sampled sites from the French Bat Monitoring Program (black square) and the gravel-sand pit sites of ROSELIERE program (white triangle)

Figure 3 .

 3 Figure 3. Relative importance of bat activity in gravel-sand pits

Figure 1 .

 1 Figure 1. Map of the distribution in France of the sampled sites from the French Bat Monitoring Program (black square) and the gravel-sand pit sites of ROSELIERE program (white triangle)

  Figure 2.

  ), arable land(A.L.), heterogeneous agricultural areas(H.A.), scrub and heathland (S.H.), dry grassland (D.G.), coniferous forest (C.F.), broadleaved forest (B.F.), mixed forest (M.F.), waterway (W.), small water courses (S.W.), large water courses (L.W.), ponds (P.), bodies of water(B.W.). Bat activity measures are abundance (i.e. number of bat pass per 6 minutes), except for E. serotinus, for whom it is the probability of contact per 6 minutes.

Appendix A: Detailed information on relationship between state of extraction or rehabilitation and vegetation characteristics of sampling point within gravel-sand pits

Local characteristics of gravel-sand pits have been defined in two ways: (i) as a categorical variable with four categories of gravel-sand pit state (during quarrying and three categories of rehabilitation according to the time elapsed after operating (<5 years; 5 years<<10 years and >10 years)) and (ii) as a categorical variable with five categories of vegetation (bare soil, seminatural grassland, bush (shrubs smaller than 7 m), woodland (trees taller than 7 m), water bodies (with water present predominantly over the year)) or

Sampling design

The protocol consists of a square of 2km-side randomly chosen (by the Museum) in a radius of 10km from the observer's home, (i.e. on average one square randomly chosen between 80 possible squares) within which ten points are chosen by the observer with at least five points representative of the habitats of the square, the other being located in 'favourable' places for bats such as river banks and wood edges, etc. These sampling design allowed to obtain a quite good correlation between proportion of habitat sampled and proportion of habitat existing at the national scale (R² = 0.95), except for urban areas which were slightly more represented in our sampling. Monitoring Program (2006Program ( -2015)).

Recording characteristic

Bats calls were detected using a

Appendix C: Bats identifications

Identifications were made by voluntary observers and then validated by Museum's scientists.

The majority of volunteers involved in the bat monitoring had participated in training courses organized since 2007, allowing high homogeneity in the identification criteria

We used Syrinx software version 2.6 [START_REF] Burt | Syrinx a software for real time spectrographic recording, analysis and playback of sound[END_REF] for spectrogram and Adobe Audition for spectral analysis and in complement we also used Scan'R (Binary Acoustic Technology, 2010) to isolate each bat vocalization and automate measure of relevant parameters [START_REF] Gannon | Call character Lexicon and analysis of field recorded bat echolocation calls[END_REF][START_REF] Obrist | Variability in echolocation call design of 26 Swiss bat species: consequences, limits and options for automated field identification with a synergetic pattern recognition approach[END_REF][START_REF] Barataud | Ecologie acoustique des chiroptères d'Europe. Identification des espèces, études de leurs habitats et comportements de chasse. Biotope, Mèze[END_REF].

Identification was made at the species level except for two genera: Plecotus sp. for which there is a lack of consensus about the acoustic criteria to use for identification at the species level [START_REF] Russ | The bats of Britain and Ireland. Echolocation calls, sound analysis and species identification[END_REF][START_REF] Obrist | Variability in echolocation call design of 26 Swiss bat species: consequences, limits and options for automated field identification with a synergetic pattern recognition approach[END_REF][START_REF] Barataud | Ecologie acoustique des chiroptères d'Europe. Identification des espèces, études de leurs habitats et comportements de chasse. Biotope, Mèze[END_REF] and Myotis sp. because of the very low occurrence of each single Myotis species and some uncertainties on acoustic identification at the species level [START_REF] Obrist | Variability in echolocation call design of 26 Swiss bat species: consequences, limits and options for automated field identification with a synergetic pattern recognition approach[END_REF][START_REF] Barataud | Ecologie acoustique des chiroptères d'Europe. Identification des espèces, études de leurs habitats et comportements de chasse. Biotope, Mèze[END_REF]. Note that the Plecotus and the Myotis group primarily included species considered to be gleaners, which capture the majority of their prey from substrates in cluttered environments (Arlettaz et al., 2001). These species eat mainly diurnal Brachyceran Diptera and non-volant arthropods such as weevils, lepidopteran larvae, harvestmen and spiders [START_REF] Audet | Foraging behavior and habitat use by a gleaning bat, Myotis myotis (Chiroptera : Vespertilonidae)[END_REF][START_REF] Swift | Gleaning as a foraging strategy in Natterer's bat Myotis nattereri[END_REF]Dietz et al., 2007), while the "aerial hawking bats", that include Pipistrellus, Eptesicus serotinus and Nyctalus species, mainly search the sky for prey [START_REF] Schnitzler | From spatial orientation to food acquisition in echolocating bats[END_REF][START_REF] Holderied | Echolocation range and wingbeat period match in aerial-hawking bats[END_REF].

The main relevant parameters used were:

- single Myotis species and some uncertainties on acoustic identification at the species level [START_REF] Obrist | Variability in echolocation call design of 26 Swiss bat species: consequences, limits and options for automated field identification with a synergetic pattern recognition approach[END_REF][START_REF] Barataud | Ecologie acoustique des chiroptères d'Europe. Identification des espèces, études de leurs habitats et comportements de chasse. Biotope, Mèze[END_REF]. In addition, due to some overlap between acoustic repertoires of the pair P. kuhlii and P. nathusii or for the pair Eptesicus serotinus and Nyctalus leisleri and for the pair Pipistrellus pipistrellus and Pipistrellus nathusii it was not possible to assign the exact species with certainty respectively for 36.5%, 10.2% and 0.1% of calls. For more details on the composition of each group, see Supplementary material 2.

Appendix D: Assessment of Habitat Specialization species index and community specializations indices

Habitat Specialization species index were assessed using data provided by the car transect survey, the second protocol of the French Bat Survey (for additional information on this protocol, see Azam et al. 2016).

French Bat Survey.

Volunteer-based standardized monitoring schemes have been widely implemented in Europe and North America (Jiguet et al., 2012). In France, the National Museum of Natural History (MNHN) initiated the French Bat Monitoring Program (FBMP) in 2006. This scheme offers a dataset of 6774 sites with both habitat characterizations and bat identifications (28 species and 960 500 bat calls).

Counting methods

The FBMP offers keen volunteers to count bats twice a year: once during the period 15th June to 31st July, and a second time during the period 15th August to 31st September. Two different versions are proposed: count point and road survey by car. We used the road survey method to assess the Specialization species index (SSI). The choice of the road circuit is delegated to the volunteers because the main constraint is related to their safety. The circuit must be done at night at low speed (recording at constant speed: 30 ± 5km/h), this excludes non paved roads, roads with a lot of traffic and high-speed roads. Only volunteers with their local knowledge of the field are able to identify such roads. All roads are thus of similar width, around 10 meters. Observers were asked to choose a road circuit of at least 30 km and located in a 10 km radius around their house. The circuit must not overlap itself. The second requirement is to design a circuit which crosses, as much as possible, the different habitats present in the area proportionally to their representativeness. To avoid biases in habitat sampling (we assume that observers would tend to follow rich habitats), the MNHN validates the circuit and defines randomly a starting point. Starting from this point, the circuit is divided into ten 2-km road segments, separated by 1-km road segments in which no recording is done.

This sampling design allows to obtain a quite good correlation between proportion of habitat sampled and proportion of habitat existing at the national scale (R² = 0.94), except for urban areas which were slightly more represented in our sampling.

Assessment of specializations indices

In the French national bat monitoring volunteers were involved in collecting habitat variable on a detailed and adapted basis. Habitat information is recorded on the first reconnaissance visit to the circuit. The appropriate habitat codes are chosen from an established hierarchical system allowing to describe more than 950 habitat types, which is very similar to widely used habitat code in bird monitoring schemes (see [START_REF] Crick | A bird-habitat coding system for use in Britain and Ireland incorporating aspects of land-management and human activity[END_REF]

Specialization species index (SSI)

We quantified the species specialization index (SSI), which is the degree of habitat specialization for a species, as the coefficient of variation (SD/mean) of its densities across habitats following Julliard et al. 's approach (2006). SSI is thus independent to species habitat preferences. However, it is also possible to assess the species specialization to forest habitats by calculating the average density of a species inventoried in forest habitats divided by the average density in non-forest habitats.

Assessment of bat community specializations indices

The Community Specialisation Index (CSI) is calculated as the arithmetic mean of the species specialization index (SSI) of the species detected, weighted by the abundances (Julliard et al., 2006):

where n is the total number of species recorded, aij is the abundance of individuals of species i (with a SSI specialization index) in segment j (Devictor et al., 2008).

The CSI reflects the relative abundance of more or less specialized species in local assemblages and is therefore expected to decrease following the relative declines of specialists (species with a high SSI). For the analyse, we kept only sites with a non-null abundance because a null CSI does not describe a generalist community.

LITTERATURE CITED

Azam, C., Le Viol, I., Julien, J.

Appendix E: Model selection for modelling bat activity between habitats


Christian Kerbiriou
email: kerbiriou@mnhn.fr

Jean François Julien

Sophie Monsarrat

Philippe Lustrat

Alexandre Haquart

Alexandre Robert

Information on population trends and biological constraints from bat counts in roost cavities: a twenty-two-year case study of a Pipistrelle bats (Pipistrellus pipistrellus, Schreber

Keywords: Pipistrellus pipistrellus, Population dynamics, count monitoring, deterministic matrix model, Stochastic-individual-based population model, disturbance

Context: According to the current trend of biodiversity loss, information on population trends at large temporal and spatial scales is necessary. However, well-documented animal population dynamics are generally based on intensive protocols requiring animal manipulation, which can be impossible to conduct in species for which conservation is a concern.

Aims: For many bat species, an alternative approach entails performing an appropriate analysis of counts in roost cavities. Because of managers' perception of chaotic variations through time, relatively few count monitoring surveys are regularly analysed. Here, we present the analysis of a twenty-two-year survey of a large hibernaculum of pipistrelle bats (Pipistrellus pipistrellus) located in a railway tunnel in Paris, France.

Methods: We propose that using combinations of population dynamics modelling using demographic parameters from the literature and statistical analyses helps with identifying the biological and methodological effects underlying the dynamics observed in census analyses.

Key results: we determined that some of the observed year-to-year variations of population size cannot be explained only by the intrinsic dynamics of the population. In particular, in 1993-1994, the population size increased by >40%, which should have implied a massive immigration. This change coincided with the end of the operation of the railway line. After consideration of a drastic trend of population decline (7%/year) we were able to detect this event and several environmental effects. Specifically, the winter conditions and the temperature in July affected the colony size, presumably because of aggregative behavior and reproduction success, respectively.

Conclusions: Emigration-immigration processes might have preponderant effects on population dynamics. In addition, we our analysis demonstrates that (1) the study population suffered a large decline (2) a combination of human disturbance and meteorological variation explains these dynamics; (3) Emigration-immigration processes have preponderant effects on the population dynamics, Implications: To conduct a meaningful analysis of non standard time series and provide a source of data for implementing biodiversity indicators, it is necessary to include (1) the local knowledge of the people involved in the field surveys in these analyses (the existence of disturbances and site protections) and (2) meteorological information for the appropriate seasons of the year.

Introduction

In the current context of the drastic erosion of biodiversity, "unprecedented additional efforts would be needed to achieve a significant reduction in the rate of biodiversity loss at all levels" (Biodiversity Synthesis of the Millennium Ecosystem Assessment (MEA 2005). To reach this target, the efforts undertaken by each country should be assessed. In Europe, the implementation of the Convention on Biological Diversity has been outlined by the Streamlining European Biodiversity Indicators (SEBI) initiative that proposes a first set of indicators to monitor the progress in Europe (European Environment Agency, 2009). The first set of this indicator can be considered "direct" core biodiversity indicators based on population trends and the diversity of a group of species [START_REF] Balmford | The 2010 challenge: data availability, information needs and extraterrestrial insights[END_REF] or the Red List Index [START_REF] Butchart | Using Red List Indices to measure progress towards the 2010 target and beyond[END_REF].

Well-documented animal population dynamics studies are generally based on quantitative methods allowing unbiased and independent estimations of survival, fecundity and dispersal rates and subsequent projection modelling using these specific rates [START_REF] Beissinger | Population viability analysis[END_REF]. However, the acquisition of such data requires intensive protocols (e.g., capture-mark-recapture protocols to estimate survival and/or dispersal rates). These methods, often involving animal handling, such as capture-recapture, could be controversial approaches when the species are endangered and/or sensitive to disturbance and could also affect the results [START_REF] Saraux | Reliability of flipper-banded penguins as indicators of climate change[END_REF], particularly with regard to bats [START_REF] Punt | Round table discussion on bat conservation proceeding of the Second International Bat Research Conference 3-4[END_REF][START_REF] Dietz | Effects of forearm bands on horseshoe bats (Chiroptera: Rhinolophidae)[END_REF]). In addition, such time-consuming methods require highly qualified personnel and can hardly be extended to a large number of sites and species.

Most of the European bat populations have a poor conservation status because of various pressures, such as the loss of suitable foraging habitats [START_REF] Walsh | Foraging habitat preference of vespertilionid bats in Britain[END_REF]Kunz and Fenton 2003), agricultural intensification [START_REF] Swanepoel | Energetic effects of sublethal exposure to lindane on pipistrelle bats (Pipistrellus pipistrellus)[END_REF][START_REF] Wickramasinghe | Bat activity and species richness on organic and conventional farms: impact of agricultural intensification[END_REF], urbanisation [START_REF] Kurta | Bat Community Structure in an Urban Park[END_REF][START_REF] Loeb | Relationship between urbanization and bat community structure in national parks of the southeastern U[END_REF]) and forest management [START_REF] O'donnell | Conservation status and causes of decline of the threatened New Zealand long-tailed bat Chalinolobus tuberculatus (Chiroptera: Vespertilionidae)[END_REF]. Human activities strongly reduce the availability of underground sites used by bats for breeding or/and hibernation. Whereas some underground sites are filled in, blocked up or transformed [START_REF] Mitchell-Jones | Protecting and managing underground sites for bats[END_REF], others are opened for tourism activities, resulting in recurrent disturbances. Such activities may have major consequences on the population dynamics of bat species at large scales since (1) several studies have stressed the high sensitivity of bats to human disturbance (Mc Craken 1989;[START_REF] Speakman | Effects of Disturbance on the Energy Expenditure of Hibernating Bats[END_REF][START_REF] Gore | Decline in the Winter Population of Gray Bats (Myotis grisescens) in Florida[END_REF]; (2) in some cases, the loss of a single site can affect the dynamics of bat populations over areas of several thousands of square kilometers [START_REF] Mitchell-Jones | Protecting and managing underground sites for bats[END_REF]. Within this context, an increasing number of bat populations occurring in roost cavities are protected and regularly counted (see the Conservation Trust and Eurobat annuals reports). However, because of the managers' perception that hibernacula counts exhibit chaotic variations over time, only relatively few hibernacula counts are regularly analysed, which, in turn may lead to the abandonment of such monitoring. Nevertheless, efforts have been made to analyse count data provided by volunteers in the context of breeding roost surveys and to provide sound assessment of population trends [START_REF] Warren | Monitoring trends in bat populations through roost surveys: methods and data from Rhinolophus hipposideros[END_REF]. Less effort has been devoted so far to hibernaculatum monitoring, despite the availability of hibernaculatum count data and the need for conservationists to detect population declines when formulating management decisions [START_REF] Trombulak | Population trends of wintering bats in vermont[END_REF]Frick et al. 2010). [START_REF] O'shea | Monitoring trends in bat populations of the United States and territories: status of the science and recommendations for the future[END_REF] advocated that new techniques must be explored and modern statistical designs applied in order to improve the scientific basis for conclusions about future bat population trends. Some recent studies and reports have considered hibernaculatum count data to assess population variations (see [START_REF] Prendergast | Trends in abundance of hibernating bats in a karst region of the southern great plains[END_REF]European Environment Agency 2013) A better understanding of the biological information included in these time series evaluations could allow (1) to design and propose of more efficient count protocols (e.g., which environmental variable to record at monitoring sites), (2) to detect population trends and then provide efficient biodiversity indicators, and (3) to assess the impact of management actions (such as fitting a grille across the hibernaculatum entrance permitting the free passage of bats but not people, Provision of additional roosting places, etc.)

The purpose of this study is to investigate how simple, specific count-based datasets can be used in combination with standard ecological methods and generic demographic data to understand the processes underlying the observed population dynamics. If count data from roosts in winter can be considered as a reliable proxy of a local population's size (for sedentary species), we hypothesize that we will be able to detect the effects of meteorological conditions on local population dynamics. Weather and food availability are known to be highly correlated with each other and with parturition in insectivorous bats (Arlettaz et al. 2011), which is in turn related with reproductive success and survival of newly volant young [START_REF] Tuttle | Population Ecology of the Gray Bat (Myotis Grisescens): Factors Influencing Growth and Survival of Newly Volant Young[END_REF]. Therefore, during the reproductive period, local bad weather conditions such as low temperature or important rainfall should affect the reproductive success and then impact negatively population size in winter, and, subsequently, count data. However, if population dynamics are only assessed through roost count data (and not with e.g., variation in demographic parameters), meteorological effects may be masked by (1) a population trend (such as a large decline), (2) an aggregative behavior linked with winter condition [START_REF] Mumford | Population Turnover in Wintering Bats in Indiana[END_REF][START_REF] Sandel | Use and selection of winter hibernacula by the eastern pipistrelle (Pipistrellus subflavus) in Texas[END_REF]) and (3) human disturbance.

Local population dynamics do not only rely on intrinsic processes (mortality and fecundity) but may also be more or less strongly influenced by immigration or emigration processes. Although disantangling the roles of intrinsic dynamics and immigration/emigration is not possible with count data, however based on a good knowledge of the species' demography it is possible to detect changes that cannot be explained only by intrinsic dynamics and involve necessary events of immigration or emigration. We first used population dynamics models with a set of generic demographic parameter values available from the literature to construct a realistic distribution of expected annual growth rates in the absence of emigration/immigration. In a second step, we compared this expected distribution (which only depends on the life history traits of the species and its capacity of intrinsic population growth) with the observed annual growth rates to detect important immigration-emigration events or local catastrophic events, such as epizootics (which is not an exclusive hypothesis) [START_REF] Blehert | Bat White-Nose Syndrome: An Emerging Fungal Pathogen?[END_REF].

After these exploratory steps, we conducted a statistical modelling to test the following assumptions:

(1) Favorable meteorological conditions such as higher temperatures during the reproductive period should positively influence counts from roost in following winter (larger number of young produced), whereas unfavorable meteorological conditions such as strong precipitation should have a negative impact. (2) Cold temperatures in winter may lead to increased counts from roosts (in the same winter), due to aggregative behavior. (3) human disturbance in the roost should adversely affect counts.

We believe that applying this simple approach to bat count data will allow a better understanding of the biological information contained in available time series.

We focused on a large population of common pipistrelle bats (Pipistrellus pipistrellus, Schreber) that was monitored for 22 years in an urban area.

MATERIALS AND METHODS

Study area

From 1991 to 2012, we monitored the population size of a large hibernaculum of pipistrelle bats (Pipistrellus pipistrellus) located in a railway tunnel in Paris, France. This railway tunnel was in service until 1993. The bat counts were conducted in the winter by the same observers during the entire period. The counting method is a direct visual count of individuals who are located in shallow notches. These notches are expansion joint vertical depth of 10 cm between concrete slabs (see supplementary material S1). The count procedure leads thus to very thin measurements errors, because all individuals are observable. This hibernaculum is one of the most important for the species in France and the only one currently known wintering site inside the city of Paris [START_REF] Lustrat | Un important gîte d'hibernation de chauves-souris à Paris (France)[END_REF]. Although it is possible that other unknown hibernaculums exist in Paris or in its immediate surroundings, common pipistrelles are generally found singly or in small numbers in crevices of buildings and trees in winter [START_REF] Dietz | Franckh-Kosmos-Naturfüher Verlargs[END_REF]). Thus, if existing, other hibernaculums are probably scarce and small.

Population dynamics modelling

To discriminate between the roles of intrinsic dynamics (fecundity and mortality) and yearly emigration-immigration processes on the population dynamics, we used a combination of deterministic and stochastic models for population dynamics.

Deterministic matrix model

In a first step, we used a one-sex, deterministic, age-classified Leslie-matrix model [START_REF] Caswell | Matrix population models. Construction, analysis and interpretation[END_REF] to infer the equilibrium intrinsic population properties (in particular, the asymptotic time-invariant population growth rate). This model was implemented using the ULM software [START_REF] Legendre | ULM, a software for conservation and evolutionary biologists[END_REF][START_REF] Ferrière | Matrix population models applied to viability analysis and conservation: Theory and practice using the ULM software[END_REF]. We considered a two-age class model (Fig. 1.; [START_REF] Sendor | Population dynamics of the pipistrelle bat: effects of sex, age and winter weather on seasonal survival[END_REF] with the following parameter values obtained from the literature: the first reproduction occurring in the first year [START_REF] Schober | Die Fledermäuse Europas[END_REF][START_REF] Dietz | Franckh-Kosmos-Naturfüher Verlargs[END_REF]; the first year survival probability, s0, was set to 0.53 [START_REF] Sendor | Population dynamics of the pipistrelle bat: effects of sex, age and winter weather on seasonal survival[END_REF]; the adult survival probability, sad, varied from 0.37 to 0.80 [START_REF] Thompson | Longevity and survival of female pipistrelle bat (Pipistrellus pipistrellus) on the Vale of York, England[END_REF]Gerell and Lundberg, 1990;[START_REF] Sendor | Population dynamics of the pipistrelle bat: effects of sex, age and winter weather on seasonal survival[END_REF] and the average female productivity, F, varied from 0.58 to 0.988 [START_REF] Webb | Population dynamics of a maternity colony of the pipistrelle bat (Pipistrellus pipistrellus) in north-east Scotland[END_REF][START_REF] Barclay | Variation in the reproductive rate of bats[END_REF]). In many respects, bats have relatively slow life histories [START_REF] Barclay | Variation in the reproductive rate of bats[END_REF]) thus one can expect small growth rate variations and this modelling approach aims to assess a range of realistic values for annual growth rates.

Approximate position of figure 1 Stochastic, individual-based population model

In addition, to compare the actual observed annual growth rates with their theoretical distribution under demographic stochasticity in the absence of immigration and emigration, we developed a stochastic two-sex individual-based population model. This model allowed the complete description of all of the individuals in terms of sex and age. In each time interval (year), adult individuals were randomly paired according to a polygynous mating system with an unrestricted harem size, i.e., we assumed that all mature females present in the population can reproduce provided that there was at least one male in the population [START_REF] Legendre | Demographic stochasticity and social mating system in the process of extinction of small populations: the case of passerines introduced to New Zealand[END_REF]). This hypothesis is realistic, as recent results suggest that the proportion of breeding females among adult females is usually very high (about 95%, see [START_REF] Barclay | Variation in the reproductive rate of bats[END_REF]. The reproductive success of each pair was determined according to a Bernoulli drawing of parameter F (in cases where F<1.0), or a Poisson trial of parameter F (in cases where F≥1). The sex of each newborn individual was randomly determined according to a 1:1 mean sex ratio.

Reproduction was followed by the differential mortality of individuals according to age-specific annual survival rates (S0 and Sad). Each individual survival event was drawn from a Bernoulli function. The parameters used were the same as for the deterministic matrix models. Three scenarios were considered (pessimistic, median and optimistic) using either the minimal, median or maximal values of Sad and F obtained from the literature [START_REF] Thompson | Longevity and survival of female pipistrelle bat (Pipistrellus pipistrellus) on the Vale of York, England[END_REF][START_REF] Gerell | Sexual differences in survival rates of adult pipistrelle bats (Pipistrellus pipistrellus) in South Sweden[END_REF][START_REF] Webb | Population dynamics of a maternity colony of the pipistrelle bat (Pipistrellus pipistrellus) in north-east Scotland[END_REF][START_REF] Sendor | Population dynamics of the pipistrelle bat: effects of sex, age and winter weather on seasonal survival[END_REF][START_REF] Barclay | Variation in the reproductive rate of bats[END_REF]). For each scenario, the changes in the population size were investigated for 1000 independent random population trajectories drawn over a fixed time horizon (22 years). The distributions of the ratios of population size at a time t (Nt) / population size at a time t-1 (Nt-1) were then compared to the observed ratios. At time zero, the population trajectories were assumed at the demographic equilibrium (stable age-class distribution and balanced sex ratio), with a total population size equal to the observed population size in 1991. In each model trajectory, years with Nt <20 individuals were excluded to avoid an inflation of the variance in the growth rates due to a strong sampling effect (see e.g., Lande et al. 2003), which would have precluded the comparison with the actual data (the observed population sizes were in the range of 350-1500).

Analysis of year-to-year variation and trend in population size. Effect of weather conditions and human disturbance.

We examined temporal variations in the number of bats counted in the hibernaculatum by (1) testing for a (decreasing or increasing) trend in numbers over the study period

; (2)
testing for an effect of the railway traffic on bat numbers. The railway tunnel was in service until 1993; since traffic can substantially affect roost attractiveness, we included this factor in our statistical analysis as a binary variable (presence or absence of railway traffic). (3) Finally, to assess the effect of weather conditions on the winter population size, we tested the existence of correlations between the count data of bat and several weather variables. Some meteorological variables, such as the winter conditions, are expected to influence hibernating bat aggregation in certain favourable hibernacula, such as tunnels, which become more attractive when the conditions are extreme. Other meteorological variables, such as the precipitation or temperature levels, recorded the year before the winter bat counts were expected to influence the reproductive success and survival of young [START_REF] Grindal | The Influence of Precipitation on Reproduction by Myotis Bats in British Columbia[END_REF][START_REF] Zahn | Reproductive success, colony size and roost temperature in attic-dwelling bat Myotis myotis[END_REF]) and, thus, affect the population size the following winter. The weather data were obtained from two websites: Infoclimat and European Climate Assessment and Dataset.

Statistical analysis

As we expected that some weather variables might be correlated with each other or might show trends over the period considered, we used Spearman's rank test to assess the correlation between paired samples of variables (see supplementary material S1), with the aim of avoiding the inclusion of correlated explanatory variables in statistical analyses. Weather variables in winter indeed showed strong correlations between them, as did the group of variables recorded in the spring before the winter counts (supplementary material S2). Only the variable average temperature in June showed a yearly significant increasing trend (supplementary material S2).

In a first step, we assessed the influence of each variable (yearly trend, human disturbance (railway traffic), weather conditions) on count data. In a second step, in order to take into account possible population trend that could hide the effect of human disturbance or weather conditions on bat numbers, we adjusted these variables to yearly trend using a sequential ANOVA (type I) in which the effects are tested sequentially.

When the variables exhibited a significant influence, we choose the variable that explained more of the deviance using the Akaike Information Criterion (AIC) for these two groups (winter variable and spring variable) because this criterion has the advantage of generality and can be applied further than the normal linear models [START_REF] Faraway | Extending the linear model with R, Generalized linear, miwed effects and nonparametric regression models[END_REF]. Finally, we constructed a full model including yearly trend, railway traffic and meteorological variables and we performed an AIC-based model selection by removing variables (see supplementary material S4 for details) to test if the full model was the most parsimonious choice. We used Generalised Linear Models (GLMs) with Poisson error distribution due to the nature of the data (count) [START_REF] Crawley | The R book[END_REF]) and we account for over-dispersion following [START_REF] Faraway | Extending the linear model with R, Generalized linear, miwed effects and nonparametric regression models[END_REF] recommendations (note that similar results were obtained with GLM with negative binomial error distribution).

We also carried out an alternative approach (see supplementary material S3), in which we took into account simultaneously all variables (trend, railway traffic, weathers conditions), using Hierarchical Partitioning (HP, R package hier.part). This approach allowed us to identify the most likely causal factors of variation in bat numbers while alleviating multicollinearity problems [START_REF] Mac Nally | Regression and model building in conservation biology, biogeography and ecology: the distinction between and reconciliation of 'predictive' and 'explanatory' models[END_REF].

RESULTS

Comparison of observed growth rates and those assessed with modelling.

Considering the range of demographic parameter values available in the literature, the asymptotic time-invariant population growth rate (λ) given by our matrix model was between 0.523 and 1.065. Moreover, increasing simultaneously demographic parameters, such as fecundity or survival, rarely led to λ>1.4 (Fig. 2).

Approximate position of figure 2

The stochastic model allowed us to obtain a distribution of annual growth rates that accounted for the random fluctuations in the population size due to demographic stochasticity under the three demographically reasonable scenarios for the Pipistrelle (Fig. 3) These three contrasted scenarios are: a pessimistic scenario, S0=0.53, Sad=0.37, F=0.58; a median scenario, S0=0.53, Sad=0.59, F=0.78 and an optimistic scenario, S0=0.53, Sad=0.8, F=0.99. The 95% confidence intervals of the annual growth rates were (0.38 -0.66), (0.72 -0.86), (1.01 -1.11), respectively, for the pessimistic, median and optimistic scenarios.

Approximate position of figure 3

The comparison between these expectations and the observed annual growth rates indicated that some of the strong year-to-year increases (Nt/Nt-1>1.15) in the population size observed in the time series cannot be explained only by the intrinsic dynamics of the population without emigration-immigration process (Fig. 3) and may have implied massive immigration events. In particular, there were two years [START_REF] Lustrat | Un important gîte d'hibernation de chauves-souris à Paris (France)[END_REF]( -1994[START_REF] Zahn | Reproductive success, colony size and roost temperature in attic-dwelling bat Myotis myotis[END_REF]( -2009, Fig. 4) , Fig. 4) in which the population size increased by >40%, presumably because of a massive immigration (see the Discussion). The increase observed between 1993 and 1994 (+384 individuals) corresponds to the abandonment of the railway line crossing the tunnel occupied by the study population. As this change is very likely related to an arrival of individuals following the increased attractiveness of the site, we only considered the 1995-2012 period in our subsequent analysis.

Approximate position of figure 4

We ran an additional scenario (hereafter, the adjusted scenario) by slightly modifying the set of demographic parameters of the median scenario to yield a growth rate similar to the one observed over the 1995-2012 period (details of protocol and parameters are provided in supplementary material S3). This adjusted scenario (S0=0.57, Sad=0.69, F=0.84) predicts that the 95% confidence interval of the year-to-year growth rate should be between 0.854 and 1.013 (Fig. 3). The comparison with the observed values of the growth rate during the 1995-2012 period (grey circles in Fig. 3) indicates that only three of the observed growth rates are included in the confidence interval of this adjusted scenario, whereas eight are lower, and ten are higher.

Population trend analyses and the importance of weather on between year variations.

Over the 1991-2012 period, we did not detect any temporal autocorrelation between the yearto-year growth rates in year t and t+1 (Spearman's rank correlation test, P=0.18), this indicates the absence of a strong bias in the bat count. Indeed, when an observer overestimates (or underestimates) bat numbers in a roost in a given year, one could expect that the estimation might be lowered (or inflated) in the next year, leading to an artefact of the alternation between the decreases and increases.

When considering each variable separately, only the year appeared significant, showing a negative trend (Table 1, this model explained 53% of the deviance). When the weather variables were adjusted to the year trend, most of their p-values drastically decreased (sequential ANOVA, Table 1). According to AIC values (Table 1) and the percentage of independent variance explained provided by the Hierarchical Partitioning (see supplementary material S5), the most important variable appeared to be the yearly trend, followed by presence of railway traffic, the group of winter weather variables (particularly frost day in January) and secondarily the group of summer variables. We then retained the number of frost day in January (Frost day) for the group of winter weather variables and the temperature in July (T.July) for the group of summer weather variables. We, thus, built a complete model in which the count data (period of 1991-2012) were explained by the Year + railway traffic + Frost day + T.July . AIC-based model selection (see supplementary material S4) indicated that this full model is the most parsimonious choice. This model explained 93% of the variance in the population size (however, this high value should be considered with caution because the model is at the limit of the over-parameterization); 68% of this explained variance was explained by the year trend, 28% by the railway traffic presence or absence, 3% by number of frost day in January and less than 1% by the temperature in July of the previous year (these results are consistent with the Hierarchical Partitioning results, see supplementary material S3). The number of common Pipistrelle bats in the hibernaculum significantly declined over the period considered -1991 to 2012-(Table 1, F1,19=1416.85; P<0.001; β =-0.078 [SE] 0.006), which corresponds to drastic trend of population decline: 7%/year. In addition, we detected a significant negative effect of the railway traffic (F1,18=985.84; P<0.001; β=-0.781 [SE] 0.100), a positive effect of number of frost days in January (F1,17=116.82; P<0.001; β=0. 0.021 [SE] 0.007 Fig. 5, and positive effect of temperature recorded in July the year prior to the winter bat counts, F1,16=34.02; P<0.001; β=0. 0.027 [SE] 0.018, Fig. 5).

Approximate position of figure 5

DISCUSSION

Despite the good availability of multi-site, long-term count data for several bat species [START_REF] Mitchell-Jones | Protecting and managing underground sites for bats[END_REF], the dynamics of most monitored populations remain largely unexplored because of the conceptual and technical difficulties in discriminating the effects of multifactorial environmental disturbances, protocol artefacts and dispersal.

We propose that using combinations of population dynamics modelling even with demographic parameters from the literature and statistical analyses helps with identifying the biological and methodological effects in census analyses. Despite the managers' perception that population sizes show chaotic variations over time, we show that counts made by volunteers in hibernaculum can provide useful information on local population dynamics and on the environmental factors underlying these dynamics.

Demographic processes underlying the observed local dynamics

Using the demographic data from the literature (i.e., generic data) in combination with count and local environmental data (i.e., specific data) allowed us to define the realistic boundaries of local population variations due to intrinsic dynamics. Despite an early age at sexual maturity, the low annual fecundities reported in the literature lead to a relatively long generation length (3.9 years for the median scenario) and a relatively high sensitivity of the population growth rate to adult survival (elasticity values are respectively 0.73 and 0.27 for adult survival and fecundity, for the median scenario). Even when considering an optimistic demographic scenario that assumes high survival and fertility rates and including variations in the annual growth due to demographic stochasticity, our results suggest that some of the strong year-to-year increases in the population size could not have resulted merely from intrinsic dynamics (see Figs. 2 and3) and might imply immigration events from unknown hibernacula. In particular, we suggest that the most rapid year-to-year increase in size (i.e., the 1993-1994 period) is linked to a change in the attractiveness of this hibernaculum as a result of the end of the exploitation of the railway line. This observation underlines the impact of disturbance on the population sizes of hibernating bats. Many studies have shown the importance of disturbance on colony dynamics and sustainability (Mc Craken 1989;[START_REF] Speakman | Effects of Disturbance on the Energy Expenditure of Hibernating Bats[END_REF][START_REF] Simon | Ecology and conservation of bats in villages and town[END_REF][START_REF] Mitchell-Jones | Protecting and managing underground sites for bats[END_REF]. The very short time delay between the end of the disturbance and its consequence on the population dynamics underlines the very active prospecting behavior of bats in choosing a favourable hibernaculum each winter (see [START_REF] Simon | Ecology and conservation of bats in villages and town[END_REF]). More generally, our analysis of an adjusted scenario (which uses median demographic data from the literature that was modified to fit the growth rate observed during the 1995-2012 period) suggests that emigration-immigration processes might have preponderant effects on population dynamics.

With such an approach we were able to detect that some strong year-to-year increases could not have resulted only from intrinsic dynamics and implied immigration events. However, for smaller increases that were consistent with the maximum intrinsic population growth, we were not able to distinguish the roles of intrinsic growth and immigration. Moreover, strong year-toyear reduction in population size can be related to either strong mortality or massive emigration, with little opportunity to distinguish the source of this variation.

Population trends and environmental effects

After removing the drastic trend of population decline (7%/year) over the 1991-2012 period, we detected a negative effect of the railway traffic on number of common pipistrelles and we further revealed some effects of the winter and summer temperatures. However the incidence of meteorological variable is very thin compare to yearly trend and presence of railway traffic.

The winter effect is presumably associated with aggregation in favourable hibernacula when the winter conditions are severe, which suggests that common pipistrelles might be able to shift their winter site within the hibernating season. Several counts within the winter could, therefore, bring useful information on the extent of movements between cavities. Furthermore, correlations between the winter weather conditions and population variations within the cavity network could inform us about the specific role of each type of cavity. The slightly positive influence of the temperature and slightly negative effect of rainfall during the month of July (note that TJuly and PJuly are not correlated) is more likely linked with reproductive parameters (i.e., fledging success or/and the survival of young). This observation fit well with the Pipistrelle's cycle of life: July is a crucial period because it corresponds to fledging of young Pipistrelle and the dispersal of the breeding colony [START_REF] Arthur | Les chauves-souris de France, Belgique, Luxembourg et Suisse. Biotope, Mèze[END_REF].

Importantly, these two seasonal environmental effects were not significantly correlated with the yearly trend, which emphasises that the observed decline of the pipistrelle population is not only explained by yearly climate variations. [START_REF] Tuttle | Estimating population sizes of hibernating bats in caves and mines[END_REF] underlined that complete enumeration of hibernating bats is possible in situations where numbers of bats are not extremely large and cavities lack great surface irregularities. In larger hibernacula with bats in roosting dense clusters, the only feasible techniques involve estimating individual densities [START_REF] Thomas | Survey and census methods[END_REF]. However, the reliability of such techniques is still unknown [START_REF] Tuttle | Estimating population sizes of hibernating bats in caves and mines[END_REF]. In addition to the differences in habitat characteristics, different species of bat exhibit different behaviors in winter. Some species are easily detectable, such as Rhinolophus ssp (which hibernates suspended to ceiling), whereas other species such as Myotis daubentonii, M. bechsteinii and M. nattereri hibernate in deep cracks and are less detected. The hibernaculum studied here is an ideal case since available slots are standardized (joints between concrete slabs), which allows detecting almost all individuals.

Limitations and perspectives

We did not consider immigration-emigration in our population dynamics models, since we had no means to add realistic constraints to immigration and emigration rates. Unlike the intrinsic dynamics, which are limited by biological, species-specific constraints (i.e., maximum reproductive output of the species), immigration-emigration processes mainly depend on the context of the focal population (e.g., distance to other populations). Such wider context could be examined through a meta-population approach in which surrounding populations interacting with the focal one are explicitly modelled (in such case, emigration would be constrained by the available pool of migrants in the meta-population). Although our dataset does not allow us such larger scale modelling for the moment, current national hibernation surveillance scheme could provide such information in the future.

Recommendations

To conduct a meaningful analysis of time-series count data of bat in hiberculatum, it is necessary (i) to include the local knowledge of the people involved in the field surveys in the analyses, for example, information on the existence of disturbances (the type, magnitude and frequency) or the implementation of site protection measures should be recorded and integrated with the count data;

(ii) to include the winter weather conditions, which are very likely associated with aggregation behavior (e.g., the number of frost day in January, the average temperature of January), although they do not necessarily imply demographic consequences;

(iii) to include the spring-summer weather information collected during the season before the winter counts (e.g., the July rainfall), as such data are expected to affect reproductive parameters, which might, in turn, influence population dynamics and (iv) our analysis also strongly suggests that a multi-site approach using count data might allow strong inferences to be drawn on the intrinsic and environmental processes underlying dispersal and population dynamics. T.day is the local ambient temperature at the time of the count; T.January is the average temperature in January; T.winter is the average temperature in winter (December-January-February); T.Anomalies is the temperature anomaly observed in January relative to the average temperatures over the 1951-1989 period; Frost day is the number of frost days in January; P.June is the rainfall recorded in June of the previous year; P.July is the rainfall recorded in July of the previous year; T.June is the average temperature in June of the previous year; T.July is the average temperature in July of the previous year; Slope of the effect (β) are given for significant test.

Figure 1 :

 1 Figure 1: Life cycle of the common pipistrelle (Pipistrellus pipistrellus) modelled with Leslie's

Figure 2 :

 2 Figure 2: Values of the deterministic growth rate (λ) as a function of the adult survival and

Figure 3 :F=0Figure 5 .

 35 Figure 3: Comparison between the expected and observed annual growth. Expected

Table 1 :

 1 Effects of disturbance and meteorological variables on the estimates of number of bat.

Acknowledgements

The manuscript was edited for language use, grammar, punctuation, spelling and overall style by American Journal Experts. We are grateful to two anonymous reviewers for their constructive comments.

Supplementary material -Appendix S2: Table of correlations (Spearman's rank test) between

the pairs of weather variables used in the modelling. T.day is the local ambient temperature at the time of the count; T.January is the average temperature in January; T.winter is the average temperature in the winter (December-January-February); T.Anomalies is the temperature anomaly observed in January relative to the average temperatures over the 1951-1989 period; Frost day is the number of frost days in January; P.June is the rainfall recorded in June of the previous year; We aimed to examine an additional scenario (hereafter, adjusted scenario) as follows: (i) with the same demographic structure and properties as our median scenario (i.e., a scenario based on the most reliable demographic parameters provided by the literature) and (ii) yielding a growth rate similar to the one observed over the 1995-2010 period (0.93).

For this purpose, we kept the same transition matrix structure as the median scenario (see Figure S2.1 below, this model yields a deterministic growth λmedian=0.797), and we slightly modified the demographic parameters to obtain λadjusted=0.93. This can be achieved by multiplying the transition matrix by a constant term, α= λadjusted/λmedian=1.17, or by multiplying the demographic parameters such that all of the nonzero terms of the transition matrix are multiplied by α [START_REF] Caswell | Matrix population models. Construction, analysis and interpretation[END_REF]. This new set of parameters leads to a population with similar demographic properties as the median scenario (i.e., the same generation time and proportions of age classes at demographic equilibrium) but a different deterministic growth rate (λadjusted=0.93).

Supplementary material -Appendix S4: Model selection table