Léa Mariton
email: lea.mariton@mnhn.fr

Christian Kerbiriou
email: christian.kerbiriou@mnhn.fr

Yves Bas
email: yves.bas@mnhn.fr

Brigitte Zanda
email: brigitte.zanda@mnhn.fr

Isabelle Le Viol
email: isabelle.le-viol@mnhn.fr

Even low light pollution levels affect the spatial distribution and timing of activity of a "light tolerant" bat species

Keywords: Artificial Light At Night, Bat, Citizen science, Moonlight, Timing of activity, Skyglow

Light pollution decreases bat abundance and delays their timing of activity.

Even low light levels affect bat abundance and timing of activity.

Skyglow enhanced by cloud cover increases light impact on the timing of activity.

Light pollution can even affect "light tolerant" open-space-foraging bat species.

Reducing direct and indirect light pollution at landscape scale is an urgent need.

Introduction

Given forecasts predicting that, by 2030, global urban land cover will increase by 1.2 million km² [START_REF] Seto | Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools[END_REF], there are urgent needs to understand mechanisms underlying urbanisation effects on biodiversity [START_REF] Mckinney | Urbanization, Biodiversity, and Conservation[END_REF]. In addition to leading to an increase in impervious surfaces, threatening biodiversity hotspots [START_REF] Seto | Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools[END_REF], it also results in the emissions of stressors such as noise, chemicals, and artificial light [START_REF] Isaksson | Urbanization, oxidative stress and inflammation: A question of evolving, acclimatizing or coping with urban environmental stress[END_REF].

Artificial Light At Night (ALAN) and the resulting light pollution spreading even far from urban areas affect 23% of the globe's surface [START_REF] Falchi | The new world atlas of artificial night sky brightness[END_REF], with a rate of 2.2% of areas being newly artificially lit per year [START_REF] Kyba | Artificially lit surface of Earth at night increasing in radiance and extent[END_REF]. As it accounts for 16.5% of global electricity demands [START_REF] Zissis | Update on the status of LED-lighting world market since 2018[END_REF], it is an energetic use issue, but ALAN impacts on biodiversity are also a growing concern [START_REF] Hölker | The Dark Side of Light: A Transdisciplinary Research Agenda for Light Pollution Policy[END_REF][START_REF] Koen | Emerging threat of the 21st century lightscape to global biodiversity[END_REF][START_REF] Longcore | Ecological light pollution[END_REF].

Light pollution has been shown to impact both nocturnal and diurnal species with potential dramatic effects on individual fitness, reproduction success and ecosystem functioning [START_REF] Gaston | The ecological impacts of nighttime light pollution: A mechanistic appraisal[END_REF][START_REF] Owens | Light pollution is a driver of insect declines[END_REF][START_REF] Svechkina | The impact of artificial light at night on human and ecosystem health: A systematic literature review[END_REF]. Many studies have focused on ALAN alteration of the species' movements and spatial distributions through attraction/repulsion behaviours [START_REF] Longcore | Ecological light pollution[END_REF][START_REF] Stone | Impacts of artificial lighting on bats: A review of challenges and solutions[END_REF]. However, ALAN also impacts the species' temporal distribution by changing natural light regimes, inducing shifts in the timing of activity of many taxa. For instance, it might disrupt the timing of activity of nocturnal taxa (e.g., arthropods [START_REF] Lynn | Artificial light at night alters the activity and feeding behaviour of sandy beach amphipods and pose a threat to their ecological role in Atlantic Canada[END_REF]amphibians: Secondi et al., 2021;mammals: Rotics et al., 2011), expand the timing of activity of diurnal taxa through the night and disrupt their sleep (e.g., birds: [START_REF] Alaasam | Effects of dim artificial light at night on locomotor activity, cardiovascular physiology, and circadian clock genes in a diurnal songbird[END_REF][START_REF] Amichai | Artificial Light at Night Promotes Activity Throughout the Night in Nesting Common Swifts (Apus apus)[END_REF][START_REF] Raap | Light pollution disrupts sleep in free-living animals[END_REF], change timings of activity by inducing photoperiod-dependent behaviours outside of usual periods (e.g., birds: [START_REF] Kempenaers | Artificial Night Lighting Affects Dawn Song, Extra-Pair Siring Success, and Lay Date in Songbirds[END_REF]mammals: Le Tallec et al., 2015). Overall, the cumulative effects of ALAN on the species' behaviour and community ecology have been recognized as a threat to ecosystem functions [START_REF] Gaston | The ecological impacts of nighttime light pollution: A mechanistic appraisal[END_REF][START_REF] Longcore | Ecological light pollution[END_REF].

Developing lighting strategies to mitigate ALAN impacts on biodiversity is therefore essential [START_REF] Hölker | The Dark Side of Light: A Transdisciplinary Research Agenda for Light Pollution Policy[END_REF][START_REF] Pauwels | Adapting street lighting to limit light pollution's impacts on bats[END_REF]. Changing lighting intensity has been suggested as a possible measure [START_REF] Gaston | REVIEW: Reducing the ecological consequences of night-time light pollution: options and developments[END_REF]. However, a few studies suggest that dim light pollution levels, similar or lower to the full moonlight illuminance under clear skies (i.e., c. 0.1 -0.3 lx), might impact biodiversity [START_REF] Azam | Evidence for distance and illuminance thresholds in the effects of artificial lighting on bat activity[END_REF][START_REF] Dominoni | Long-Term Effects of Chronic Light Pollution on Seasonal Functions of European Blackbirds (Turdus merula)[END_REF][START_REF] Evans | Circadian Effects of Light No Brighter Than Moonlight[END_REF][START_REF] Secondi | Artificial light at night alters activity, body mass, and corticosterone level in a tropical anuran[END_REF].

Biological effects of widespread low light levels, induced for instance by skyglow (i.e., the artificial light scattered by atmospheric constituents and reflected back towards the Earth [START_REF] Gaston | The biological impacts of artificial light at night: The research challenge[END_REF][START_REF] Kyba | Artificially lit surface of Earth at night increasing in radiance and extent[END_REF]), are an emerging concern [START_REF] Gaston | The ecological impacts of nighttime light pollution: A mechanistic appraisal[END_REF]. Cloud cover has been shown to enhance this indirect light pollution by amplifying and expanding it to remote areas which are not affected by light pollution on clear nights [START_REF] Jechow | Imaging and mapping the impact of clouds on skyglow with all-sky photometry[END_REF][START_REF] Jechow | Mapping the brightness and color of urban to rural skyglow with all-sky photometry[END_REF][START_REF] Kyba | Worldwide variations in artificial skyglow[END_REF]. However, skyglow, and more generally, diffuse light pollution effects on biodiversity have been scarcely studied [START_REF] Kupprat | Can skyglow reduce nocturnal melatonin concentrations in Eurasian perch?[END_REF][START_REF] Torres | Artificial skyglow disrupts celestial migration at night[END_REF][START_REF] Wilson | Direct and ambient light pollution alters recruitment for a diurnal plant-pollinator system[END_REF].

As they are nocturnal, and directly exposed to light pollution, bats provide a useful system to study the impacts of ALAN on biodiversity. Natural pattern of light and dark is an important environmental cue synchronizing bat circadian rhythm [START_REF] Erkert | Ecological Aspects of Bat Activity Rhythms[END_REF]. The evening emergence of bats has been shown to be influenced by the sunset time [START_REF] Erkert | Ecological Aspects of Bat Activity Rhythms[END_REF]) while moonlight appears to influence the activity of some bat species [START_REF] Saldaña-Vázquez | Lunar phobia in bats and its ecological correlates: A meta-analysis[END_REF]. A perception of higher predation risks has been suggested as a driver of bat responses to light [START_REF] Jones | Foraging strategy and predation risk as factors influencing emergence time in echolocating bats[END_REF][START_REF] Rydell | Timing of Foraging Flights of Three Species of Bats in Relation to Insect Activity and Predation Risk[END_REF]. Hence light pollution, by disrupting natural light regimes, hiding environmental cues and potentially increasing predation risks, might have dramatic effects on both bat abundance and timing of activity.

It has been shown that bat responses to ALAN depend on their foraging strategies and flight techniques [START_REF] Jones | Foraging strategy and predation risk as factors influencing emergence time in echolocating bats[END_REF]. Narrow-space-foraging bat species (mainly shortrange-echolocators that slowly fly in confined spaces [START_REF] Denzinger | Bat guilds, a concept to classify the highly diverse foraging and echolocation behaviors of microchiropteran bats[END_REF][START_REF] Voigt | The Impact Of Light Pollution On Bats Varies According To Foraging Guild And Habitat Context[END_REF]) are considered to be light-intolerant at all spatial scales [START_REF] Lacoeuilhe | The Influence of Low Intensities of Light Pollution on Bat Communities in a Semi-Natural Context[END_REF][START_REF] Rydell | Exploitation of Insects around Streetlamps by Bats in Sweden[END_REF][START_REF] Salinas-Ramos | Artificial illumination influences niche segregation in bats[END_REF][START_REF] Spoelstra | Response of bats to light with different spectra: Light-shy and agile bat presence is affected by white and green, but not red light[END_REF][START_REF] Voigt | The Impact Of Light Pollution On Bats Varies According To Foraging Guild And Habitat Context[END_REF][START_REF] Zeale | Experimentally manipulating light spectra reveals the importance of dark corridors for commuting bats[END_REF], whereas the responses of edge-and open-space-foraging species (mainly mid-and long-range-echolocators that fly faster than narrow-space-foraging species [START_REF] Denzinger | Bat guilds, a concept to classify the highly diverse foraging and echolocation behaviors of microchiropteran bats[END_REF][START_REF] Voigt | The Impact Of Light Pollution On Bats Varies According To Foraging Guild And Habitat Context[END_REF]) to light pollution are more complex and depend on the spatial scale considered [START_REF] Pauwels | Adapting street lighting to limit light pollution's impacts on bats[END_REF][START_REF] Voigt | The Impact Of Light Pollution On Bats Varies According To Foraging Guild And Habitat Context[END_REF].

At local scale, edge-and open-space-foraging species, such as Pipistrellus spp. and Eptesicus spp., tend to be attracted by light sources [START_REF] Azam | Evidence for distance and illuminance thresholds in the effects of artificial lighting on bat activity[END_REF][START_REF] Rydell | Exploitation of Insects around Streetlamps by Bats in Sweden[END_REF][START_REF] Salinas-Ramos | Artificial illumination influences niche segregation in bats[END_REF][START_REF] Stone | Impacts of artificial lighting on bats: A review of challenges and solutions[END_REF][START_REF] Zeale | Experimentally manipulating light spectra reveals the importance of dark corridors for commuting bats[END_REF] probably because of the predictable foraging opportunities they offer by attracting high insect densities [START_REF] Owens | Light pollution is a driver of insect declines[END_REF][START_REF] Russo | Artificial illumination near rivers may alter bat-insect trophic interactions[END_REF]. However, at a slightly higher scale, [START_REF] Azam | Evidence for distance and illuminance thresholds in the effects of artificial lighting on bat activity[END_REF] showed that Serotine bats (Eptesicus serotinus, Schreber, 1774) experienced an avoidance behaviour from 25 to 50 m from streetlights probably because of a perception of higher predation risks. Few studies focus on ALAN effects on bats at landscape scale and they are not consensual regarding the responses of open-space-foraging species. [START_REF] Laforge | Reducing light pollution improves connectivity for bats in urban landscapes[END_REF] found that, at landscape scale, E. serotinus responded positively to ALAN, and [START_REF] Mathews | Barriers and benefits: Implications of artificial night-lighting for the distribution of common bats in Britain and Ireland[END_REF] found that the Lesser noctule (Nyctalus leisleri, Kuhl, 1817) was more frequent in light-polluted environments.

Conversely, [START_REF] Azam | Disentangling the relative effect of light pollution, impervious surfaces and intensive agriculture on bat activity with a national-scale monitoring program[END_REF] showed that, at landscape scale, E. serotine abundance decreased because of light pollution and [START_REF] Voigt | Movement responses of common noctule bats to the illuminated urban landscape[END_REF] showed that the spatial use of the Common noctule (Nyctalus noctula, Schreber, 1774) was largely constrained by ALAN.

Hence, bat responses to ALAN may be driven by different mechanisms according to the considered spatial scales.

Several mechanisms might explain ALAN-mediated declines in bat abundance at landscape scale: (1) ALAN could disrupt bat commuting behaviours by decreasing landscape connectivity [START_REF] Hale | The ecological impact of city lighting scenarios: Exploring gap crossing thresholds for urban bats[END_REF][START_REF] Laforge | Reducing light pollution improves connectivity for bats in urban landscapes[END_REF][START_REF] Stone | Street Lighting Disturbs Commuting Bats[END_REF][START_REF] Voigt | Movement responses of common noctule bats to the illuminated urban landscape[END_REF], (2) ALAN may interfere with insect development, reproductive success, movement behaviours and foraging behaviours [START_REF] Boyes | Is light pollution driving moth population declines? A review of causal mechanisms across the life cycle: Light pollution and moth life cycles[END_REF][START_REF] Owens | Light pollution is a driver of insect declines[END_REF], it could therefore contribute the decline of insect populations (at local scale: [START_REF] Boyes | Street lighting has detrimental impacts on local insect populations[END_REF][START_REF] Van Grunsven | Experimental light at night has a negative long-term impact on macro-moth populations[END_REF], possibly at global scale: Owens et al., 2019) and deplete landscapes of feeding resources for bats, (3) ALAN may disrupt the timing of bat nocturnal activity with potential cascading effects on their fitness and reproductive success, leading to potential population declines [START_REF] Stone | Impacts of artificial lighting on bats: A review of challenges and solutions[END_REF].

Roost illumination has been shown to delay the emergence of narrow-space-foraging bat species [START_REF] Boldogh | The effects of the illumination of buildings on house-dwelling bats and its conservation consequences[END_REF][START_REF] Duvergé | Functional significance of emergence timing in bats[END_REF][START_REF] Luo | Artificial light reduces foraging opportunities in wild least horseshoe bats[END_REF]. Some localised studies also suggest that the timing of bat activity might be disrupted at foraging sites due to ALAN. [START_REF] Haddock | Light pollution at the urban forest edge negatively impacts insectivorous bats[END_REF] highlighted that the first recording of Little forest bats (Vespadelus vulturnus, Thomas 1914, edge-space foraging) was delayed because of light pollution at forest edges and [START_REF] Stone | Street Lighting Disturbs Commuting Bats[END_REF] showed that the onset of commuting behaviour of the Lesser horseshoe bat (Rhinolophus hipposideros, Borkhausen, 1797, narrow-space-foraging species) was delayed by ALAN. Such shifts in the timing of activityobserved at foraging sitesmight result in a desynchronization of bats with the peak of activity of their prey, a reduced time-budget to forage [START_REF] Luo | Artificial light reduces foraging opportunities in wild least horseshoe bats[END_REF][START_REF] Stone | Impacts of artificial lighting on bats: A review of challenges and solutions[END_REF], and eventually it might impact their fitness and reproduction success. However, such studies are scarce, they focus on local scale and direct light pollution. Furthermore, there is a lack of studies on potential impacts of light pollution on the timing of activity of open-foraging-space species.

Intensity is an important factor to consider when studying bat responses to light pollution [START_REF] Hale | The ecological impact of city lighting scenarios: Exploring gap crossing thresholds for urban bats[END_REF][START_REF] Kerbiriou | Switching LPS to LED Streetlight May Dramatically Reduce Activity and Foraging of Bats[END_REF][START_REF] Stone | Impacts of artificial lighting on bats: A review of challenges and solutions[END_REF]. Some studies even suggest that bat spatiotemporal distribution might be disrupted by slight modifications of light levels such as those due to moonlight [START_REF] Appel | Aerial insectivorous bat activity in relation to moonlight intensity[END_REF][START_REF] Gomes | Time of night and moonlight structure vertical space use by insectivorous bats in a Neotropical rainforest: An acoustic monitoring study[END_REF][START_REF] Kolkert | Insectivorous bats foraging in cotton crop interiors is driven by moon illumination and insect abundance, but diversity benefits from woody vegetation cover[END_REF].

However, this moonlight effect has not been much studied in temperate regions and is still discussed [START_REF] Saldaña-Vázquez | Lunar phobia in bats and its ecological correlates: A meta-analysis[END_REF]. Because the skyglow maintains low light pollution levels in previously dark areas far from urban centres, it is crucial to determine if low intensities might disrupt bat spatiotemporal distribution.

In this study, we used the data from a national citizen science program to assess if light pollution, including at low intensities, affects the abundance and timing of activity of openspace-foraging bat species at their foraging sites, at landscape scale. We chose to focus on E.

serotinus, an open-space-foraging bat species which is common in France but declining [START_REF] Bas | Bat population trends[END_REF]. Because their responses to light pollution are known to be complex and scale dependent [START_REF] Azam | Disentangling the relative effect of light pollution, impervious surfaces and intensive agriculture on bat activity with a national-scale monitoring program[END_REF][START_REF] Azam | Evidence for distance and illuminance thresholds in the effects of artificial lighting on bat activity[END_REF][START_REF] Stone | Impacts of artificial lighting on bats: A review of challenges and solutions[END_REF], it is a particularly interesting species to explore the mechanisms explaining the responses of open-space-foraging bat species to ALAN. We predicted (1) that E. serotinus abundance would decrease with light intensities at foraging sites, (2) that their timing of activity at thier foraging sites would be delayed later in the night because of light pollution, (3) that moonlight and cloud cover, by modifying light intensity, would also affect E. serotinus abundance and timing of activity.

Materials and methods

2.1.Bat surveys

Vigie-Chiro program

We used data from the "stationary points protocol" of the French citizen science bat monitoring program Vigie-Chiro (https://www.vigienature.fr/fr/chauves-souris), which has been coordinated by the French National Museum of Natural History since 2014. This standardised passive acoustic monitoring-based protocol encouraged volunteers to set ultrasonic recorders on hypothetical bat foraging sites for at least one full-night. To limit heterogeneity between devices, all recorders were configured with recommended settings.

Species identification

Species identification was made with the Tadarida software which automatically detects and extracts sound parameters of recorded sound events and classifies them into classes according to a confidence index value using a random forest algorithm (https://github.com/YvesBas/Tadarida-C/ ; [START_REF] Bas | Tadarida: A Toolbox for Animal Detection on Acoustic Recordings[END_REF]. Tadarida-D was used with default settings. Tadarida-C was used through consecutively Ta_Tc.R and ContextualClassif.R with default settings and R 3. 2.3 (R Core Team, 2015).

We considered bat passes, defined as the occurrence of a single or several bat calls during a 5-s interval (Kerbiriou et al., 2019a;[START_REF] Millon | Bat activity in intensively farmed landscapes with wind turbines and offset measures[END_REF]. This metric had already been used in many studies [START_REF] Azam | Is part-night lighting an effective measure to limit the impacts of artificial lighting on bats?[END_REF][START_REF] Barré | Accounting for automated identification errors in acoustic surveys[END_REF][START_REF] Millon | Bat activity in intensively farmed landscapes with wind turbines and offset measures[END_REF][START_REF] Pauwels | Accounting for artificial light impact on bat activity for a biodiversity-friendly urban planning[END_REF], and, as 5 s is the mean call duration recorded for E. serotinus in France [START_REF] Kerbiriou | Bat Pass Duration Measurement: An Indirect Measure of Distance of Detection[END_REF], it was the best compromise between the risk of counting several times the same individual and the risk of missing another individual.

As automated identification can generate significant error rates, we chose to follow [START_REF] Barré | Accounting for automated identification errors in acoustic surveys[END_REF] approach to ensure result robustness against automated identification errors. We considered E. serotinus passes with a maximum error rate tolerance of 0.5 to minimize false positives while keeping a high number of E. serotinus passes. Then, in order to ensure result robustness, we confirmed our results using a maximum error rate tolerance of 0.1 in Supplementary material A. Such a rate permitted us to limit false positives but discarded more true positives.

Spatiotemporal restrictions

We excluded surveys that might have been carried out near bat roosts, as we expected relative abundance to be higher there and driven by other factors than at foraging sites. There, we also expected an earlier timing of activity driven by specific events such as emergence. We also excluded surveys carried out in mountain environments (defined as sites above 500 m above sea level) to restrict our dataset to E. serotinus distribution range [START_REF] Arthur | Les chauves-souris de France, Belgique, Luxembourg et Suisse[END_REF] and to avoid any bias due to mountain environments (e.g., shades, specific climate) or to bat specific behaviours in these kind of environments [START_REF] Cryan | Effect of elevation on distribution of female bats in the Black Hills, South Dakota[END_REF][START_REF] Mccain | Could temperature and water availability drive elevational species richness patterns? A global case study for bats[END_REF].

It had been shown by [START_REF] Catto | Activity patterns of the serotine bat (Eptesicus serotinus) at a roost in southern England[END_REF] that while the timing of E. serotinus activity was unimodal to bimodal during gestation, it became more complex and multimodal during lactation. Therefore, we restricted our study to the gestation period of E. serotinus (from May 1 st to 21 st June [START_REF] Catto | Activity patterns of the serotine bat (Eptesicus serotinus) at a roost in southern England[END_REF][START_REF] Harbusch | The sessile serotine: The influence of roost temperature on philopatry and reproductive phenology of Eptesicus serotinus (Schreber, 1774) (Mammalia: Chiroptera)[END_REF])) because we expected that the timing of E. serotinus activity would be consistent during this period. Moreover, during gestation, female bats experience a greater wing loading that might affect their flight performance and make them more likely to be vulnerable to predation [START_REF] Duvergé | Functional significance of emergence timing in bats[END_REF].

Therefore, bats are likely to be prone to suffer from light pollution during this period. Finally, during this period, controlling for the potential confounding effect of night length is easier, as it is only decreasing.

2.2.Biological and environmental metrics

Abundance

We used the number of E. serotinus passes (named hereinafter "relative abundance") during the night (from 30 min before sunset to 30 min after sunrise) as a proxy for abundance. As a matter of fact, because the number of feeding buzzes (i.e., call sequences produced by bats prior to a successful, or attempted, prey capture [START_REF] Griffin | Listening in the Dark[END_REF]) has been shown to be strongly related to the overall number of bat passes, relative abundance can been used as reliable estimator of foraging activity [START_REF] Put | Bats respond negatively to increases in the amount and homogenization of agricultural land cover[END_REF][START_REF] Russo | Use of foraging habitats by bats in a Mediterranean area determined by acoustic surveys: Conservation implications[END_REF][START_REF] Salvarina | Seasonal bat activity related to insect emergence at three temperate lakes[END_REF]. Furthermore, commuting and foraging are not fully distinct activities for E. serotinus [START_REF] Catto | Foraging behaviour and habitat use of the serotine bat (Eptesicus serotinus) in southern England[END_REF].

Our "relative abundance" dataset was made up of 21,452 E. serotinus passes, across 1894 full nights, on 1055 sites, from 2014 to 2020 (Fig. 1). As E. serotinus can be found across the whole French territory (except in mountain areas that we discarded from our datasets) and, as this species is highly flexible when choosing their foraging habitats [START_REF] Arthur | Les chauves-souris de France, Belgique, Luxembourg et Suisse[END_REF], we hypothesised that all our survey sites were inside the range/habitat requirements of E. serotinus. We hence kept for our analyses the nights with no E. serotinus pass.

Timing of activity

As we postulated that no metric would be robust enough with less than 10 E. serotinus passes by night, we only kept nights with at least 10 passes during the whole night. We confirmed the pertinence of such a threshold according to the metric chosen to study the timing of activity by resampling the E. serotinus passes of the 100 nights with the most passes of our dataset (Supplementary material B). Among the 1894 full nights of the "relative abundance" dataset, 488 had at least 10 E. serotinus passes and they covered 333 sites. These nights constituted our "timing of activity" dataset (Fig. 1). [START_REF] Catto | Activity patterns of the serotine bat (Eptesicus serotinus) at a roost in southern England[END_REF] showed that the timing of E. serotinus activity was unimodal to bimodal during pregnancy with a high peak after sunset and, possibly, a lower one before sunrise. We thus chose to focus only on the first part of the night (from 30 min before sunset to 4 h and 30 min after sunset) as it covered the first and higher peak of activity observed during gestation. The 488 first parts of night had 19,489 E. serotinus passes. The time of the first bat call recorded has been used in studies focusing on timings of bat activity at foraging sites [START_REF] Haddock | Light pollution at the urban forest edge negatively impacts insectivorous bats[END_REF][START_REF] Stone | Street Lighting Disturbs Commuting Bats[END_REF]. However, in studies on bat emergence from roost, the median is preferred, even if it requires to monitor bats over a longer period [START_REF] Bullock | Analysis of the timing and pattern of emergence of the pipistrelle bat (Pipistrellus pipistrettus)[END_REF]. It is less vulnerable to extreme values, as it does not rely on a single event and does not only reflect the onset of bat activity, but also its spreading across time. Therefore, to characterise the timing of activity, we chose to calculate the time of the median E. serotinus pass during the first 4 h and 30 min of the night, in seconds after sunset.

ALAN

To characterise light pollution around sites, we used radiance data (in nW.sr -1 .cm -2 , excluding lunar contamination and cloud cover degradation) from the average radiance composite raster produced by the Earth Observation Group (EOG) using night-time data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (EOG, Annual VNL V1 2016, https://eogdata.mines.edu/products/vnl/, [START_REF] Elvidge | VIIRS night-time lights[END_REF].

We hypothesised that E. serotinus spatiotemporal distribution at foraging sites would be influenced by the presence of light pollution across their whole vital domain at landscape scale (e.g., ALAN might delay their emergence from roosts and delay their arrival at foraging sites because of the barrier effect, or even result in lower feeding resources at the landscape scale). Therefore, we considered buffer zones with a 3000 m radius around the studied sites, as it covered the mean distance between foraging sites and roosts [START_REF] Catto | Foraging behaviour and habitat use of the serotine bat (Eptesicus serotinus) in southern England[END_REF][START_REF] Kervyn | Ecology and ethology of the serotine bat, Eptesicus serotinus (Chiroptera, Vespertilionidae): Perspectives for the conservation of bats[END_REF][START_REF] Robinson | Home range and habitat use by the serotine bat, Eptesicus serotinus, in England[END_REF]. We ensured that the radiance gradient of our datasets was representative of the French radiance gradient (Supplementary material C).

To ensure the robustness of our approach, we re-analysed our datasets with the radiance value at the recorder sites rather than the mean value in 3000 buffer zones around sites (Supplementary material D).

Other factors affecting light levels

We considered other meteorological and astronomical factors that might influence light levels: (1) cloud cover (extracted from the NCEP/NCAR Reanalysis dataset, [START_REF] Kalnay | The NCEP/NCAR 40-year reanalysis project[END_REF] and ( 2) moonlight (we computed a variable that synthesised moon illumination values and moonrise hours (Supplementary material E)). We confirmed that the gradients of cloud cover and moonlight were wide enough to ensure robust analyses (respectively Supplementary materials F and G).

Weather

Temperature, precipitations and windspeed are known to influence bat spatiotemporal distributions, including E. serotinus one [START_REF] Catto | Foraging behaviour and habitat use of the serotine bat (Eptesicus serotinus) in southern England[END_REF][START_REF] Vaughan | Habitat Use by Bats (Chiroptera) Assessed by Means of a Broad-Band Acoustic Method[END_REF][START_REF] Verboom | The importance of linear landscape elements for the pipistrelle Pipistrellus pipistrellus and the serotine bat Eptesicus serotinus[END_REF]. As the timing of E. serotinus activity might be influenced not only by the weather conditions of the night but also by those of previous ones (Catto, Racey, et Stephenson 1995), we considered the daily weather and the difference with previous days.

Absolute measures of temperature may be misleading if E. serotinus populations adapt to local climatic conditions: a given temperature may represent a mild day for one population but a cold day for another. We therefore analysed temperature as anomalies relative to longterm averages for each site.

Eventually, because of correlation issues, we did not include the precipitations of the day and the difference between the windspeed of the day and the windspeed of the previous days (further details on the calculation and selection of the weather variables are given in Supplementary material E).

Land-use

The higher the landscape quality for bats, the greater the relative abundance will be, and the less bats may have to commute to arrive at their foraging sites. We chose to calculate seven environmental variables known to influence the spatiotemporal distribution of bats, especially E. serotinus, in 3000 m buffer zones around sites: proportions of deciduous forest, conifer forest, grasslands and artificialized surfaces (dense and diffuse impervious surfaces, industrial and commercial estates), habitat diversity (Shannon's diversity index), density of small woody features, minimum distance from freshwater. The buffer zones around the sites of our datasets covered the same land-use type gradient as buffer zones around sites randomly selected in France. Correlation issues led us not to include road density and proportion of crops despite their potential effects on the spatiotemporal distribution of bats (Supplementary material E).

ALAN and artificialized surfaces were highly correlated (Pearson correlation coefficient equal to 0.88 for the "relative abundance" dataset and 0.83 for the "timing of activity" dataset). However, as this study aimed at assessing if ALAN by itself might impact E. serotinus spatiotemporal distribution, we had to consider these two variables. Thus, we chose to adapt our statistical modelling methods (see below) to consider both artificialized surfaces and ALAN despite their correlation.

2.3.Statistical analyses

Full models

We used Generalized linear mixed models (GLMM) to test the influence of light level on the biological metrics (R 4.0.4 (R Core Team, 2021), R package glmmTMB). We used a negative binomial distribution with a quadratic parameterization for "relative abundance" analyses and a gaussian distribution for "timing of activity" analyses.

We included all variables previously described in our models as fixed effects along with Julian day and its quadratic effect to control any potential effect of the night length or of the gestation progress. For "relative abundance" analyses, we added the recorder type used as a fixed effect, to control the different performances of recorders in detecting bats. All quantitative fixed effects were scaled, so that the regression coefficients calculated would be comparable in their effects and magnitudes [START_REF] Schielzeth | Simple means to improve the interpretability of regression coefficients[END_REF].

We tested several interactions that could affect light levels: interaction (1) between cloud cover and ALAN as cloud cover might amplify light pollution [START_REF] Jechow | Imaging and mapping the impact of clouds on skyglow with all-sky photometry[END_REF][START_REF] Kyba | Worldwide variations in artificial skyglow[END_REF], ( 2) between moonlight and ALAN as, for instance, light pollution could be so strong that moonlight does not have an effect on bats anymore, (3) between moonlight and cloud cover as the latter could conceal the moon. Note that we also added an interaction between temperature anomaly of the day and difference with temperature anomalies of the previous days because bat responses to temperature extremes may depend upon whether previous days have also been too hot or cold to forage effectively.

Our dataset had a spatiotemporal structure: (1) a site might have been monitored several nights, (2) if these nights were consecutive, they formed a single "participation" (i.e., a single monitoring session during which the same recorder stayed at the same place during at least one full night to several in a row); if they were not consecutive, they formed several "participations". Thus, we included a random effect on participations nested on sites for "relative abundance" analyses. For "timing of activity" analyses, the smaller dataset did not allow the use of such a random structure. As we already considered Julian day, we did not include the random effect on participation but we kept the random effect on sites.

We hypothesised that, the more E. serotinus passes there would be during the night, the more accurate the calculation of the metric used to characterise the timing of activity would be. We therefore put a weight on the logarithm of the number of E. serotinus passes during the first 4 h and 30 min after sunset for the analyses on the timing of activity.

The 3000 m buffer zones around some sites of our datasets overlapped, however, according to [START_REF] Zuckerberg | A Review of Overlapping Landscapes: Pseudoreplication or a Red Herring in Landscape Ecology?[END_REF], overlapping landscapes are not a violation of independence and they do not induce nor protect from spatial autocorrelation. There was some spatial autocorrelation for both the "relative abundance" and the "timing of activity" analyses. We added latitude as a fixed effect to correct it. As some spatial autocorrelation remained for the "timing of activity" analyses, we corrected it by adding an autocovariate computed with the autocov_dist function (R package spdep).

The full models were the following ones (all variables are summarized in Table H; model assumptions were checked according the procedure described in Supplementary material I): Metric: "relative abundance" or "timing of activity" metric *: only for "relative abundance" analyses **: only for "timing of activity" analyses

Model averaging

We chose the model averaging approach so that we could assess both the effects of artificialized surfaces and ALAN despite their correlation. The aim was to compare their relative importance on the relative abundance and timing of activity.

Eq. ( 1)

We processed all the models resulting from all the combinations of the fixed effects with this condition: never include artificialized surfaces and ALAN in the same combinations (i.e., never include these two variables in the same models) (R package MuMIn and snow).

For "relative abundance" analyses, we always included latitude (to correct spatial autocorrelation) and recorder type (to control possible bias). For "timing of activity" analyses, we always included latitude and the autocovariate (to correct spatial autocorrelation). Then, a model averaging was computed within a ∆AICc (second order bias correction for Akaike Information Criterion) of six points [START_REF] Burnham | AIC model selection and multimodel inference in behavioral ecology: Some background, observations, and comparisons[END_REF][START_REF] Grueber | Multimodel inference in ecology and evolution: Challenges and solutions: Multimodel inference[END_REF][START_REF] Richards | Dealing with overdispersed count data in applied ecology: Overdispersed count data[END_REF]. Since the inclusion of models with interaction terms involving ALAN might favour selection of ALAN over artificialized surfaces, we repeated all analyses excluding those terms and found similar results as those obtained with interaction terms (Supplementary material J).

To assess if the variables had an effect on the relative abundance or the timing of activity, we compared the relative importance of the variables (i.e., the sum of weights (SW)). However, as it has been shown that only considering this criterion is hazardous, we crossed it with the 95% confidence intervals of regression coefficients obtained with the model averaging [START_REF] Galipaud | Ecologists overestimate the importance of predictor variables in model averaging: A plea for cautious interpretations[END_REF]. Hence, we considered that a variable had an effect when the confidence interval of its regression coefficient did not overlap zero and its SW was above 0.6.

We checked the robustness of our results by comparing them to those we would have obtained by only considering the best model and the significance of the estimates included in it, and we found concordant results. We also confirmed that not discarding complex versions of any other model with a lower AICc value (as suggested by [START_REF] Richards | Model selection and model averaging in behavioural ecology: The utility of the IT-AIC framework[END_REF], was not an issue in our analyses. Furthermore, to ensure that our results were sound against the multicollinearity issues raised by [START_REF] Cade | Model averaging and muddled multimodel inferences[END_REF], we also computed model averaging on standardised estimates based on partial standard deviations for their variables and found similar results as with a "classical" standardisation of estimates (see Supplementary material K for these additional analyses).

Results

3.1.Relative abundance

ALAN had a strong negative effect on relative abundance. It was the variable with the greatest effect size of all those tested (Table 1) (see Table L for details on the model averaging results) and its SW was much greater than the artificialized surfaces one. For an average mid-sized town (mean radiance 7.8 nW.sr -1 .cm -2 , Table M), there was 18% less E. serotinus passes than in a dark place (radiance = 0 nW.sr -1 .cm -2 ; assuming all other variables held at mean levels).

When considering the ALAN value at the recorder sites rather than the mean ALAN value in the 3000 m buffer zones, the AICc of the best model was higher and artificialized surfaces had a greater SW than ALAN (Supplementary material D). The estimate (-0.014) and confidence interval (-0.020 ; -0.007) of ALAN when considering ALAN at the recorder sites were nonetheless similar to those obtained when considering the mean ALAN value in the 3000 m buffers zones (Table 1).

Moonlight also had a negative impact on relative abundance while there was no clear effect of cloud cover and interactions.

Besides variables reflecting light levels around sites, relative abundance increased with favourable meteorological conditions (high temperature, higher temperature than the previous days, less rain than the previous days), with Julian day and with habitats known to Table 1: Model averaging results for a ∆AICc of six points for the "relative abundance" and "timing of activity" analyses: estimate, sum of weights (SW) and 95% confidence interval (CI) for each variable (apart from latitude and recorder type that were fixed for "relative abundance" analyses and latitude and the autocovariate that were fixed for "timing of activity" analyses) (estimates in bold when the 95% confidence interval did not overlap zero and the SW was above 0.60). All quantitative fixed effects were scaled and estimates were standardized by dividing them by the standard deviation of the response variable.

Relative abundance

Timing of activity

3.2.Timing of activity

Increased ALAN delayed the timing of activity, and this delay was increased by a higher cloud cover (Table 1, Figure 2, Figure N). For an average mid-sized town (mean radiance 7.8 nW.sr -1 .cm -2 , Table M), activity was delayed by 6 minutes on a clear night and by 10 minutes on a night with a 50% cloud cover, compared to a site with no ALAN (radiance = 0 nW.sr - 1 .cm -2 ; assuming all other variables held at mean levels). Where there was no ALAN, increased cloud cover provoked an earlier activity, whereas above an ALAN value of 31.04 nW.sr -1 .cm -2 , the cloud cover seemed to delay the timing of activity.

Moonlight also delayed the timing of activity. However, this effect was weakened by increasing ALAN (Table 1, Figure 3,Figure O). Compared to a night with no moonlight (0%), a moonlight of 50% delayed activity by 4 minutes at the average mid-sized town, and by 9 minutes at a site with no ALAN (assuming all other variables held at mean levels).

Above an ALAN value of 15.40 nW.sr -1 .cm -2 , the moonlight effect even seemed to shift the timing of activity earlier.

When considering the ALAN value at the recorder sites rather than the mean ALAN value in 3000 m buffer zones, the AICc of the best model was higher and these two interactions no longer had any significant effect (Supplementary material D).

The timing of activity was not affected by any of the land-use variables, in particular, artificialized surfaces were not included in any models of the model set. The timing of activity was delayed by favourable meteorological conditions (higher temperature than the previous days, less rain than the previous days, less wind) and varied according to Julian day (Julian day led to an earlier activity until approximatively the two-third of the period considered, then it delayed activity) (Table 1).

Discussion

This study is one of the first to test natural and artificial light effects on both the spatial and temporal distributions of an open-space-foraging bat species at their foraging sites, at landscape scale. Light pollution reduced E. serotinus relative abundance and delayed their timing of activity. The use of a seven-year citizen science database allowed us to consider a whole national territory and gave us the unique opportunity to show the impact of fine light intensity variations (moonlight, skyglow amplified by cloud cover) on E. serotinus spatiotemporal distribution.

4.1.Relative abundance

At landscape scale, ALAN was responsible for a decrease in E. serotinus relative abundance at their foraging sites. The obtained results when considering ALAN at local scale confirmed that this decrease in abundance was not the reflection of a localised avoidance behaviour.

Such results are consistent with [START_REF] Azam | Disentangling the relative effect of light pollution, impervious surfaces and intensive agriculture on bat activity with a national-scale monitoring program[END_REF] study results on open-space-foraging bat species. Using a different dataset from the Vigie-Chiro program (data from one-hour car surveys), they found that E. serotinus abundance was lower when exposed to light pollution at landscape scale. On the contrary, [START_REF] Laforge | Reducing light pollution improves connectivity for bats in urban landscapes[END_REF] found that E. serotinus had a positive response to light pollution at a city scale. The authors hypothesized that in their highly urbanized study sites, with few optimal foraging areas, streetlights might have become suboptimal foraging areas; this could explain the difference between their own results and those obtained by [START_REF] Azam | Disentangling the relative effect of light pollution, impervious surfaces and intensive agriculture on bat activity with a national-scale monitoring program[END_REF].

Furthermore, we found that even the low light levels created by moonlight reduced E. serotinus abundance. In South America, some authors found that moonlight affected bat abundance making it higher or lower depending on the species [START_REF] Appel | Aerial insectivorous bat activity in relation to moonlight intensity[END_REF][START_REF] Gomes | Time of night and moonlight structure vertical space use by insectivorous bats in a Neotropical rainforest: An acoustic monitoring study[END_REF][START_REF] Vásquez | Species-specific effects of moonlight on insectivorous bat activity in central Chile[END_REF]. However, to our knowledge, this study is one of the first to show such an effect, called "lunar phobia", on the abundance of a European open-spaceforaging bat species. [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] detected a decreasing abundance of Daubenton's bat (Myotis daubentonii, Kuhl 1817), an edge-space-foraging species, when exposed to moonlight but they did not detect any effect on E. serotinus. This result difference can be explained by the fact that they did not consider the hours of moonrise in their analyses.

Furthermore, they began to record bats 30 min after sunset. If moonlight impacted the early activity, it might therefore not have been detected. Overall, the effect we found of moonlight on abundance indicates that even low, occasional or periodic increases of light levels could result in lower E. serotinus abundance.

The decrease of an open-space-foraging species abundance when exposed to light, despite potential positive impacts locally, could be explained by several mechanisms. In the short-term, light might impact bat abundance by modifying prey availability. For instance, insect abundance has been shown to vary according to moonlight [START_REF] Bowden | The influence of moonlight on catches of insects in light-traps in Africa. Part II. The effect of moon phase on light-trap catches[END_REF][START_REF] Williams | Effect of Moonlight on Insect Activity[END_REF] and [START_REF] Lang | Activity levels of bats and katydids in relation to the lunar cycle[END_REF] linked White-throated round-eared bat (Lophostoma silvicolum, D'Orbigny, 1836) higher abundance during new moon compared to full moon periods to a higher activity of the katydids they prey on. Furthermore, a perception of increased predation risks when exposed to light has also been suggested as a potential driver of bat responses to light [START_REF] Jones | Foraging strategy and predation risk as factors influencing emergence time in echolocating bats[END_REF][START_REF] Rydell | Timing of Foraging Flights of Three Species of Bats in Relation to Insect Activity and Predation Risk[END_REF]. This may result in changes of the timing and duration of bat activity during bright nights to limit predation risks.

In this context, the tolerance of open-space-foraging bat species to light pollution when foraging could only be the result of a local trade-off between their energetic needs and the risk of predation, the higher prey concentrations around light sources offsetting greater risks of being seen by predators.

When bright conditions are created by moonlight, bats may be able to compensate their lower activity during those bright nights by being more active during darker ones. But, when these bright conditions are due to ALAN, they are constant, and bats could then either not be able to reach their energetic needs in the long-term or be compelled to be active despite higher predation risks. It could result in lower individual fitness and dramatic disruptions of population dynamics.

Furthermore, in the medium-and long-terms, light pollution might not only impact bat fitness, but also the fitness of the insect they eat. Some authors suggested that ALAN may be a driver of insect population declines in light-polluted areas [START_REF] Boyes | Street lighting has detrimental impacts on local insect populations[END_REF][START_REF] Grubisic | Insect declines and agroecosystems: Does light pollution matter?: Insect declines and agroecosystems[END_REF][START_REF] Van Grunsven | Experimental light at night has a negative long-term impact on macro-moth populations[END_REF] or even globally [START_REF] Owens | Light pollution is a driver of insect declines[END_REF]. Therefore, light pollution may affect bat abundance by decreasing the overall available feeding resources at landscape scale.

Eventually, light pollution might not only disrupt bat foraging behaviours, but also their commuting ones. For instance, [START_REF] Hale | The ecological impact of city lighting scenarios: Exploring gap crossing thresholds for urban bats[END_REF] showed that P. pipistrellus movements were restricted in brightly lit gaps, ALAN creating a barrier effect impairing landscape connectivity. Bats may hence have to find longer routes to reach their foraging sites with potential greater energetic costs that can affect their individual fitness and, in fine, their abundance [START_REF] Stone | Street Lighting Disturbs Commuting Bats[END_REF]. If the energetic costs of alternative routes are too high, ALAN might even result in a reduction of the accessible lands to forage for bats at landscape scale.

4.2.Timing of activity

Increased ALAN delayed the timing of activity, and this delay was increased by higher cloud cover when considering ALAN at landscape scale. Firstly, the overall ALAN delaying effect we found is consistent with the few and localised studies focusing on edge-and narrow-spaceforaging bat species at foraging sites [START_REF] Haddock | Light pollution at the urban forest edge negatively impacts insectivorous bats[END_REF][START_REF] Stone | Street Lighting Disturbs Commuting Bats[END_REF] which also showed that ALAN delayed the timing of activity, our study expanding it to open-spaceforaging species at wide scale. Secondly, cloud cover amplifying the ALAN effect at landscape scale is consistent with studies showing that skyglow (i.e., diffuse light pollution glow at landscape scale, even affecting areas that are not directly lit [START_REF] Kyba | Artificially lit surface of Earth at night increasing in radiance and extent[END_REF]) is amplified during overcast nights [START_REF] Jechow | Imaging and mapping the impact of clouds on skyglow with all-sky photometry[END_REF][START_REF] Kyba | Worldwide variations in artificial skyglow[END_REF]. By amplifying skyglow, cloud cover can thus increase the effects of ALAN on wildlife [START_REF] Van Hasselt | Cloud cover amplifies the sleep-suppressing effect of artificial light at night in geese[END_REF]. On the contrary, where there was no ALAN, cloud cover shifted the timing of activity earlier likely by darkening the night sky in rural locations [START_REF] Jechow | Evaluating the summer night sky brightness at a research field site on Lake Stechlin in northeastern Germany[END_REF]. Hence, dynamic and fine variations of light levels affect the timing of E. serotinus activity.

Interestingly, moonlight also delayed the timing of activity. However, this effect was weakened by increasing ALAN. Such results suggest that light pollution masks other luminous environmental cues. It also shows that even periodic or occasional increases of light levels could impact E. serotinus timing of activity.

The delayed timing of activity around light-polluted foraging sites could be explain by several hypotheses. First, bat emergence from roosts might be delayed because of ALAN, as

shown by a few studies on narrow-space-foraging species [START_REF] Boldogh | The effects of the illumination of buildings on house-dwelling bats and its conservation consequences[END_REF][START_REF] Duvergé | Functional significance of emergence timing in bats[END_REF][START_REF] Luo | Artificial light reduces foraging opportunities in wild least horseshoe bats[END_REF][START_REF] Mcaney | Activity patterns of the lesser horseshoe bat Rhinolophus hipposideros at summer roosts[END_REF]. Also, as light pollution is known to decrease landscape connectivity for bats [START_REF] Hale | The ecological impact of city lighting scenarios: Exploring gap crossing thresholds for urban bats[END_REF][START_REF] Laforge | Reducing light pollution improves connectivity for bats in urban landscapes[END_REF][START_REF] Stone | Street Lighting Disturbs Commuting Bats[END_REF], a delayed timing of activity at foraging sites could be the result of longer flights to reach them. Then, if bats arrive later, they might potentially suffer from a desynchronization with the peak of activity of their prey [START_REF] Luo | Artificial light reduces foraging opportunities in wild least horseshoe bats[END_REF]. It could result in a reduced efficient time-budget (i.e., a reduced period during which bats may feed on the prey their diets are mainly composed of) and/or in longer foraging durations to reach their energetic needs.

Delayed timing of activity could potentially lead to a reduced efficient time-budget to forage for bats and/or higher energetic costs to forage. If these delays are occasional, for instance because of brighter nights caused by moonlight, bats may be able to compensate potential harmful effects by taking advantage of darker nights to reach their energetic needs.

However, as light pollution is a constant stressor, delays caused by ALAN may eventually prevent bats from reaching their energetic needs in the medium-and long-terms, which could have cascading effects on individual fitness and population dynamics, and thus result in lower bat abundance at landscape scale when exposed to ALAN. For instance, [START_REF] Boldogh | The effects of the illumination of buildings on house-dwelling bats and its conservation consequences[END_REF] showed that juveniles of narrow-space-foraging bat species were smaller in illuminated buildings, where bat emergence was delayed because of ALAN. However, our study only focuses on the gestation period and further investigations should be carried out for the lactation onewhen energetic needs are even higherto assess whether ALAN still has an effect on the timing of E. serotinus activity.

4.3.Management consequences

Abundant and widespread bats such as E. serotinus provide important ecosystem functions [START_REF] Mathews | Barriers and benefits: Implications of artificial night-lighting for the distribution of common bats in Britain and Ireland[END_REF]. [START_REF] Tiede | Seasonal variation in the diet of the serotine bat (Eptesicus serotinus): A highresolution analysis using DNA metabarcoding[END_REF] showed that, among the most frequent taxa E. serotinus fed on, there were many potential pests of forestry and agriculture, this bat species therefore contributing to biological control. More generally, they suggested that E. serotinus contributes to the stabilization of food webs and ecosystems, by exploiting seasonally abundant insect prey. Hence, ALAN impacts on E. serotinus spatiotemporal distribution may have dramatic consequences on the ecosystem services they provide and might, more generally, have harmful effects on ecosystem functioning.

These effects of light levels on the spatiotemporal distribution of an open-space-foraging bat species show that even species considered to be "light tolerant", that mainly roost in buildings [START_REF] Marnell | Protection of overground roosts for bats[END_REF], can suffer from light pollution. Because bat species of the same foraging guild tend to respond to ALAN in a similar way [START_REF] Voigt | The Impact Of Light Pollution On Bats Varies According To Foraging Guild And Habitat Context[END_REF], other open-space-foraging bat species are likely to suffer from similar impacts of light pollution on their abundance and timing of activity. Narrow-space-foraging species that are known to be particularly sensitive toward ALAN [START_REF] Rydell | Exploitation of Insects around Streetlamps by Bats in Sweden[END_REF][START_REF] Voigt | The Impact Of Light Pollution On Bats Varies According To Foraging Guild And Habitat Context[END_REF] and/or species that usually roost in trees may experience even more drastic effects. It stresses the urge to reduce light pollution to protect bats, and more generally biodiversity. [START_REF] Gaston | REVIEW: Reducing the ecological consequences of night-time light pollution: options and developments[END_REF] suggested five levers to reduce light pollution: prevent dark areas from being lit, limit the duration of artificial lighting, reduce light trespass, reduce light intensity and change ALAN spectral composition. Bats are known to present different responses to light with different spectra [START_REF] Barré | Bats seek refuge in cluttered environment when exposed to white and red lights at night[END_REF][START_REF] Lewanzik | Transition from conventional to light-emitting diode street lighting changes activity of urban bats[END_REF][START_REF] Spoelstra | Response of bats to light with different spectra: Light-shy and agile bat presence is affected by white and green, but not red light[END_REF][START_REF] Straka | The effect of cave illumination on bats[END_REF]. However, in this study, we could not assess how different spectral compositions would have affected our results, as the light pollution data available at landscape scale were not made of multiple spectral bands. Hence, further studies would particularly be necessary to explore how ALAN spectral composition may modify how light pollution affects the timing of bat activity at landscape scale.

Limiting the lighting duration might only be efficient if part-night lighting schemes overlap with the range of bat activity (for instance streetlights should be switched off during emergence and during the first and higher foraging peak), which is not the case today [START_REF] Azam | Is part-night lighting an effective measure to limit the impacts of artificial lighting on bats?[END_REF][START_REF] Day | Part-night lighting: Implications for bat conservation: Part-night lighting and bats[END_REF]. As even low light intensities (similar to moonlight) could disrupt bat spatiotemporal distribution, the intensity under which light stops affecting bats might be very low. Therefore, even if reducing light intensity might reduce light impacts on bats, it might not be a very efficient measure. Our study, by highlighting that, at landscape scale, bats suffer from light pollution and its intensity variation due to cloud cover, shows the need of lighting installations that reduce horizontally-and upward-directed lighting, and more generally light trespass.

Conclusion

This study highlights that the abundance and timing of activity of an open-spaceforaging bat species, at foraging sites, are both affected by light pollution at landscape scale.

It stresses that even species often considered to be "light tolerant" could suffer from ALAN.

The intensity under which light stops impacting bat activity could be very low as moonlight, cloud cover and the amplifying of skyglow during overcast nights seem to impact the spatiotemporal distribution of bats. By showing that the bat abundance was reduced and the timing of bat activity was delayed when exposed to light, our study raises the urge to investigate further how delayed timings of activity might affect individual fitness, reproduction success and eventually result in population dynamic disruptions.

Fig. 1 :

 1 Fig. 1: Data processing and construction of the biological metrics.

  Metric ~ ALAN + Conifer_forest + Deciduous_forest + Grasslands + Artificialized_surfaces + Habitat_diversity + Small_woody_features + Min_distance_freshwater + Temperature + Difference_temperature + Windspeed + Difference_precipitations + Cloud_cover + Moonlight + Julian_day + Julian_day² + Recorder_type* + Temperature:Difference_temperature + Moonlight:Cloud_cover + Moonlight:ALAN + Cloud_cover : ALAN + Latitude + autocov** + (1| site/participation)* + (1|site)** With:

Fig. 2 :

 2 Fig. 2: Interaction between ALAN and cloud cover: Predicted values and 95% confidence

Fig. 3 :

 3 Fig. 3: Interaction between moonlight and ALAN: Predicted values and 95% confidence

Further

  research would be needed to determine if this decrease in abundance at landscape scale when exposed to ALAN results from a redistribution of E. serotinus populations in darker places at a wider scale and/or from lower individual fitness which might lead to population declines. In particular, it is worth noting that[START_REF] Bas | Bat population trends[END_REF] showed that E. serotinus population declined by -30% between 2006 and 2019 in France. It raises the question of the causes of such a strong decline and, what role light pollution could be playing.

Acknowledgements

This work was funded by the Institut de la Transition Environnementale de l'Alliance Sorbonne Université (SU-ITE). We thank Kévin Barré for helping us checking the robustness of our results according to different identification success thresholds and for his numerous advices. We are also grateful for Nolwenn Le Touz's help with proofreading. We thank CC-IN2P3 and PCIA-MNHN for providing computing and storage facilities, and Didier Bas for his help in this process. The success of such a large-scale study relies on the continuous participation of the volunteers of the Vigie-Chiro program, who we warmly thank. We also thank the two anonymous reviewers for all their insightful comments on the manuscript.

Data availability statement

The data supporting this study are available at https://doi.org/10.5281/zenodo.6418651 .

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

Supplementary material A: Consistency of the results obtained for datasets built with a maximum error rate tolerance of 0.5 with datasets built with a maximum error rate tolerance of 0.1 Supplementary material B: Threshold on the number of E. serotinus passes for the "timing of activity" analyses Supplementary material C: Comparison of the French radiance gradient with the radiance gradient in our datasets Supplementary material D: Influence of the spatial scale at which the ALAN metric is calculated Supplementary material E: Details the calculation and selection of environmental variables Supplementary material F: Gradient of cloud cover for the studied nights Supplementary material G: Gradient of moonlight for the studied nights Table H: Variables extracted to control exogenous factors that could impact E. serotinus relative abundance and timing of activity at their foraging site. The variables that have been discarded due to multi-collinearity issues are in brackets. Ab = "relative abundance" dataset, Ta = "timing of activity" dataset. Supplementary material I: Checks of model assumptions Supplementary material J: Analyses when considering full models without interactions including ALAN Supplementary material K: Checking of the robustness of the model averaging results

Table L: Results of the model averaging for the "relative abundance" and the "timing of activity" analyses. Even if a lot of models were selected in these analyses, the differences between the AICc of the null model and the AICc of the best model were always high.

Table M: Mean of the mean radiances (in nW.sr -1 .cm -2 ) of the French municipalities according to their population size (only municipalities that are below 500 m above sea levels are considered).

Fig. N: Interaction between cloud cover and ALAN:

Predicted values and 95% confidence intervals of the timing of activity (i.e., the time of the median E. serotinus pass during the first half of the night) with all variables equal to zero (i.e., all variables equal to their mean, as they were previously scaled) apart from cloud cover and ALAN. This graph represents the median time of activity according to cloud cover (back transformed in %) for three values of ALAN (2.2 nW.sr -1 .cm -2 being the mean radiance of French municipalities of 1000 to 5000 inhabitants and 7.8 nW.sr -1 .cm -2 being the mean radiance for municipalities of 5000 to 10,000 inhabitants, see Table M).