Anne Mimet

Christian Kerbiriou

Laurent Simon

Jean-Francois Julien

Richard Raymond

Contribution of private gardens to habitat availability, connectivity and conservation of the common pipistrelle in Paris

Keywords: Greenveining, bats, urban policies, land use complementation, ecological network, Circuitscape

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Urbanization is one of the main drivers of the biodiversity crisis, leading to the erosion of species diversity [START_REF] Mcdonald | The implications of current and future urbanization for global protected areas and biodiversity conservation[END_REF][START_REF] Olden | Forecasting faunal and floral homogenization associated with human population geography in North America[END_REF], a decrease in both total abundance in communities [START_REF] Newbold | Global effects of land use on local terrestrial biodiversity[END_REF][START_REF] Pellissier | Relative importance of the land-use composition and intensity for the bird community composition in anthropogenic landscapes[END_REF] and in the number of individuals of most species (C. G. [START_REF] Threlfall | Sensitivity of insectivorous bats to urbanization: Implications for suburban conservation planning[END_REF], and biotic homogenization [START_REF] Mckinney | Urbanization as a major cause of biotic homogenization[END_REF]. The underlying mechanisms include direct loss of natural habitat [START_REF] Devictor | Functional biotic homogenization of bird communities in disturbed landscapes[END_REF][START_REF] Devictor | Functional homogenization effect of urbanization on bird communities[END_REF], as well as disconnection of the habitat patches of populations, thus impeding movement [START_REF] Clauzel | Coupling a landscape-based approach and graph theory to maximize multispecific connectivity in bird communities[END_REF][START_REF] Tannier | Impact of urban developments on the functional connectivity of forested habitats: A joint contribution of advanced urban models and landscape graphs[END_REF]. Depending on their size, composition, configuration and management, urban green areas have the potential to support wildlife populations by providing habitat and by contributing to the connectivity of natural populations [START_REF] Alberti | The effects of urban patterns on ecosystem function[END_REF][START_REF] Muratet | Contrasting impacts of pesticides on butterflies and bumblebees in private gardens in France[END_REF][START_REF] Muratet | The role of urban structures in the distribution of wasteland flora in the Greater Paris area, France[END_REF][START_REF] Pellissier | Birds are also sensitive to landscape composition and configuration within the city centre[END_REF][START_REF] Politi Bertoncini | Local gardening practices shape urban lawn floristic communities[END_REF][START_REF] Shwartz | Outstanding challenges for urban conservation research and action[END_REF]. There is increasing recognition that urban green areas have ecological value [START_REF] Breuste | Applying landscape ecological principles in urban environments[END_REF][START_REF] Goddard | Scaling up from gardens: biodiversity conservation in urban environments[END_REF], a recognition going along with a call to develop a better understanding of the roles of urban green areas in biodiversity in order to guide conservation actions within urban areas [START_REF] Dearborn | Motivations for Conserving Urban Biodiversity[END_REF][START_REF] Shwartz | Outstanding challenges for urban conservation research and action[END_REF].

The benefits of urban green areas are tracked by urban authorities and policies, which favor different types of actions to promote urban biodiversity such as ecological management (e.g., delay mowing the grass in the parks to live time to insects and plans for reproduction), reduction of pesticides and maintaining and developing ecological corridors, as in London, Dublin, Berlin or Paris (City of Berlin, 2012;City of Dublin, 2016;City of London, 2016;Conseil de Paris, 2018;Ville de Paris, 2017). These policies aim to make cities crossable and livable to natural populations, usually by targeting the larger public green areas but overlooking private ones, such as gardens [START_REF] Evans | Colonisation of urban environments is associated with reduced migratory behaviour, facilitating divergence from ancestral populations[END_REF][START_REF] Goddard | Scaling up from gardens: biodiversity conservation in urban environments[END_REF]). Yet gardens provide significant amounts of green areas and resources for wildlife in urban areas [START_REF] Cameron | The domestic garden -Its contribution to urban green infrastructure[END_REF][START_REF] Davies | A national scale inventory of resource provision for biodiversity within domestic gardens[END_REF], complementing large public green areas such as parks by increasing habitat availability and connectivity [START_REF] Colding | Ecological land-use complementation" for building resilience in urban ecosystems[END_REF][START_REF] Loram | Urban domestic gardens ( XII ): The richness and composition of the flora in five UK cities[END_REF][START_REF] Melles | Urban bird diversity and landscape complexity: Species-environment associations along a multiscale habitat gradient[END_REF][START_REF] Rudd | Importance of backyard habitat in a comprehensive biodiversity conservation strategy: a connectivity analysis of urban green spaces[END_REF]. However, our understanding of this complementation process remains incomplete. We do not have estimates or a general understanding of the relative contributions of gardens and public green areas to habitat availability and connectivity in cities, especially considering that said contributions are expected to be species-dependent [START_REF] Lepczyk | Biodiversity in the City: Fundamental Questions for Understanding the Ecology of Urban Green Spaces for Biodiversity Conservation[END_REF] and configuration-dependent [START_REF] Goddard | Scaling up from gardens: biodiversity conservation in urban environments[END_REF]. Urban ecology literature has stressed the importance of different scales (i.e. local to the landscape scale) and of vegetation structure and heterogeneity in explaining the distribution of species and diversity in an urban context [START_REF] Goddard | Scaling up from gardens: biodiversity conservation in urban environments[END_REF][START_REF] Goddard | Why garden for wildlife? Social and ecological drivers, motivation and barriers for biodiversity management in residential landscapes[END_REF][START_REF] Lepczyk | Biodiversity in the City: Fundamental Questions for Understanding the Ecology of Urban Green Spaces for Biodiversity Conservation[END_REF][START_REF] Melles | Urban bird diversity and landscape complexity: Species-environment associations along a multiscale habitat gradient[END_REF]. Getting accurate estimates of the relative contributions of gardens and public areas to habitat availability and connectivity therefore requires multiscale analyses including vegetation structure and heterogeneity.

Bats are one of the few strictly protected mammals living within urban environments (they are included in Annex IV Council Directive 92/43/EEC, 1992). Previous researches have shown the detrimental effects of urbanization on bat populations [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] Walsh | Foraging Habitat Preferences of Vespertilionid Bats in Britain Author ( s ): Allyson L . Walsh and Stephen Harris Source[END_REF] but certain bat species occur in cities, using trees planted along streets and parks as urban substitutes for their natural foraging habitat Some species use man-made structures for breeding roosts and can live in cities if other basic requirements, like access to water, are also met [START_REF] Marnell | Protection of overground roosts for bats[END_REF][START_REF] Simon | Ecology and conservation of bats in villages and town[END_REF]. [START_REF] Oprea | Do wooded streets provide connectivity for bats in an urban landscape?[END_REF][START_REF] Threlfall | Ecological processes in urban landscapes: Mechanisms influencing the distribution and activity of insectivorous bats[END_REF]. As long-lived insectivorous species with a slow reproductive rate, bats are considered good indicators of the response of biodiversity to anthropogenic pressure [START_REF] Jones | Carpe noctem: The importance of bats as bioindicators[END_REF]. The strength of the impacts of urbanization on bats appears to be context-dependent, i.e., the degree of urbanization, the amount of vegetation remaining and patch connectivity have been shown to largely explain observed distribution patterns [START_REF] Oprea | Do wooded streets provide connectivity for bats in an urban landscape?[END_REF][START_REF] Threlfall | Ecological processes in urban landscapes: Mechanisms influencing the distribution and activity of insectivorous bats[END_REF].

Among common bat species, Pipistrellus pipistrellus (common pipistrelle) is one of the most abundant in North European urban areas [START_REF] Gaisler | Habitat preference and fight activity of bats in a city[END_REF][START_REF] Hale | Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large uk conurbation[END_REF][START_REF] Lintott | Differential responses to woodland character and landscape context by cryptic bats in urban environments[END_REF].

With the goal of evaluating the benefits of including private green areas (i.e. gardens) in urban conservation initiatives, this study aims to quantify the respective contributions of public and private green areas to habitat availability and connectivity for the common pipistrelle, focusing the analysis on the city of Paris.

The study focuses on testing three hypotheses. First, we hypothesize that the bat pass abundance depends on the vegetation spatial heterogeneity and on the area and height of vegetation and buildings, at different spatial scales. Because of their large size, we secondly hypothesize that public green areas are the most important contributors to the availability of habitat area for the common pipistrelle, only marginally complemented by private green areas. Because of their scattered spatial configuration, we thirdly hypothesize private green areas to be the main providers of habitat connectivity in the city, providing the bats with stepping-stone connectivity across the urban matrix between larger habitat patches centred on public green areas.

 14m² of public green area / inhabitant (21m² for Berlin, 68m² for Madrid, 31m² in average for the large french cities)  450 public green areas (parcs, gardens, promenades …)

Methods

Study area

The study was conducted in intramural Paris, a densely populated city of 105 km² (21,067 inhab/km² in 2014) in the heart of the Greater Paris region. Intramural Paris refers to the central part of this agglomeration, bounded by the Périphérique ring-road, and administered by the Mairie de Paris (city council). Built areas are dominated by low-rise buildings of six to seven floors (i.e., 18 to 30 meters high) [START_REF] Pellissier | Birds are also sensitive to landscape composition and configuration within the city centre[END_REF]. The number and size of green areas is low compared to most other European big cities. The percentage of public green space is about 9.5% of the Paris area, while it is around 18.8% in Brussel and 38.9% in Rome (http://www.worldcitiescultureforum.com). Two woods -Vincennes (9.95 km², east of Paris), and Boulogne (8.5 km², west of Paris)are the largest green areas in the city, bringing some nature right into the heart of Paris (Figure 2). These two woods are known to house roosts of large viable populations of the common pipistrelle, while very little is known about roosts location in intramural Paris. This study therefore considers these two woods as viable source habitat patches of the common pipistrelle, that can be connected by foraging movement or dispersal. We model the foraging-commuting habitat availability and connectivity between these woods through the rest of Paris, acoun.

Methods overview

The general method applied in the paper is to quantify the respective contributions of public and private green areas to habitat availability and connectivity for the common pipistrelle by comparing its habitat availability and connectivity in a scenario that includes all of the green areas in Paris (the All green areas scenario) one that includes only public green areas (the Only public green areas scenario). To do so, we organized the workflow of the methods in three steps, following the three hypotheses detailed in the introduction. In a first step, we fit a model explaining the abundance of common pipistrelle echolocation calls using environmental variables. In a second step, we estimate foraging-commuting habitat availability for the common pipistrelle by using the fitted model to predict the pass abundance for the All green areas and Only public green areas scenarios. We isolate the contribution of private green area to foraging-commuting habitat availability for the common pipistrelle by comparing the foraging-commuting habitat availability values obtained under the two scenarios. In a third step, we directly derive conductance from predicted foragingcommuting habitat availability and estimate habitat connectivity under the two scenarios using a circuit modeling approach. We isolate the contribution of private green area to habitat connectivity of the common pipistrelle by comparing the connectivity values obtained under the two scenarios.

Step 1: Modeling and predicting bat pass abundance in Paris

Bat sampling

We produced foraging-commuting habitat availability and connectivity maps for P. pipistrellus using data from the French Bat Monitoring Programme (FBMP) for 2008 to 2013.

The FBMP is coordinated by the French National Museum of Natural History and follows a standardized data recording methodology [START_REF] Kerbiriou | Common bats are more abundant within Natura 2000 areas[END_REF] (Appendix S1). The sampling scheme consists of randomly chosen 2x2 km squares from a 2x2 km grid. Within each square, observers selected and visited 10 points: at least five of these points were representative of the habitats of the square and the others were located in 'favorable' places for bats such as along the edge of woods. Each point was sampled using a continuous recording of 6 minutes and the ten points of a site were sampled on the same night and always in the same order at each visit. Observers recorded bats only when weather conditions were favorable (i.e., no rain, temperature higher than 12°C and wind speed of less than 5 m/sec; Appendix S1). Observers conducted the sampling during peak daily activity, i.e. beginning thirty minutes after dusk (FBMP recommendations). It generally took less than 3 hours to sample the 10 recording points of the square [START_REF] Vandevelde | Activity of European common bats along railway verges[END_REF]. Data was recorded from 2008 to 2013, between the 16 th June and the 5 th August, during the reproduction period. We extracted the 224 intramural Parisian points from the FBMP database for 2008 to 2013 (Figure 1). Depending on observers' availability over the years, the sampling effort at each point varied from one to five years. The dataset included 552 recordings at 224 points (139 points in 2008, 158 points in 2009, 72 points in 2010, 30 points in 2011, 68 points in 2012, 77 points in 2013).

We cannot distinguish individual bats from their echolocation calls, making it impossible to calculate absolute bat density, so we used the number of bat passes recorded every 6 minutes as a measure of bat activity (for more detail see Appendix S1). A bat pass is defined as one or more bat echolocation calls during a sound recording of 1.2 s at × 10 time expansion (see Appendix S1 for the methodology used to detect the number of bat passes).

The identification of the common pipistrelle does not raise issue in Paris, where species overlapping on acoustic repertoires (such as Pipistrellu. pygmaeus or Miniopterus scherbersii) do no occur. The duration of the recording (1.2 s) is predefined by the ultrasound detector (Tranquility Transect; David Bale, Courtpan. Design Ltd, Cheltenham,UK) [START_REF] Roche | A car-based monitoring method reveals new information on bat populations and distributions in Ireland[END_REF]. We used bat activity as a proxy of habitat suitability in terms of food resources and accessibility, hereafter called foraging-commuting habitat [START_REF] Frey-Ehrenbold | Landscape connectivity, habitat structure and activity of bat guilds in farmland-dominated matrices[END_REF][START_REF] Pinaud | Modelling landscape connectivity for greater horseshoe bat using an empirical quantification of resistance[END_REF][START_REF] Raino | Summer foraging habitats of bats in a Mediterranean region of the Iberian Peninsula Relating Echolocation Calls to Bat Species[END_REF][START_REF] Russo | Use of Foraging Habitats by Bats in a Mediterranean Area Determined by Acoustic Surveys : Conservation Implications Author ( s ): Danilo Russo and Gareth Jones Published by[END_REF]. Our data showed zero-inflation and were highly overdispersed, with a lot of sites with zero pass and very few over 4 passes, the maximum being 60 passes in a site. In order to account for over-dispersion in the statistical analyses, we applied an adapted method (Hurdle model, see dedicated section) and thresholded the maximum pass abundance at 4, meaning that recordings with more than 4 bat passes were attributed a number of 4. For all analyses, we averaged the abundance of bats passes observed per sample point over the different years.

Creating variables for built areas and vegetation

We described the vegetation and built environment of Paris on a raster grid of 2m resolution. We used a set of 18 built areas and vegetation variables to around each pixel or the raster (see below for description and in Appendix S2). We chose variables known to influence the probability of observing the common pipistrelle because of their power to indicate resource availability, roosting opportunities, movement facilitation, or avoidance behaviour. Each variable was computed for three radii around the pixel, i.e., 20 m, 200 m and 500 m, to account for very local (street and garden scale, choice of the local flying route) to foraging home-range-scale processes. 20 m corresponds to the minimum detection distance for the echolocation signal of search flight (i.e. echolocation calls before prey detection) (Barataud, 2015;[START_REF] Kalko | Plasticity in Echolocation Signals of European Pipistrelle Bats in Search Flight : Implications for Habitat Use and Prey Detection[END_REF]. 200 m and 500 m are in the order of magnitude of the common pipistrelle home range during the reproduction period, as 75% of the foraging activity occurs in a radius of 100 m and 100% in a radius of 750 m (Davidson-Watts, Walls, & [START_REF] Davidson-Watts | Differential habitat selection by Pipistrellus pipistrellus and Pipistrellus pygmaeus identifies distinct conservation needs for cryptic species of echolocating bats[END_REF][START_REF] Nicholls | Contrasting home-range size and spatial partitioning in cryptic and sympatric pipistrelle bats[END_REF]. Because Paris is a small geographic area (about 12*9 km) with a high density of sampling points (224), 500 m was also a good compromise to capture larger home-range scale processes while limiting extreme overlap between the larger buffers around the sampling points. [START_REF] Parisien D'urbanisme | APUR, données de référence[END_REF]. We also obtained the location of the public green areas from the APUR website (Atelier Parisien d'Urbanisme, 2016). The location of the private green areas was estimated by subtracting the vegetation of public green areas from overall vegetation. In order to provide a broad overview of the respective spatial organization of public and private green areas in Paris, we computed three simple landscape metrics from the raw data: total area, total number of patches and average area of patches, a patch being defined as a unit composed of adjacent pixels of vegetation. For this simple descriptive analysis, a patch of green area was defined as continuous cells covered by vegetation.

Variables describing the vegetation

We computed four different variables based on vegetation height to describe the vegetation environment of the pixel. P. pipistrellus is known to respond to vegetation: it typically commutes at a height of ~3-10 m [START_REF] Berthinussen | Do bat gantries and underpasses help bats cross roads safely?[END_REF][START_REF] Verboom | Effects of food abundance and wind on the use of tree lines by an insectivorous bat, Pipistrellus pipistrellus[END_REF]; it tends to avoid open habitats and vegetation higher than 3m mitigates the negative effects of urbanization [START_REF] Hale | Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large uk conurbation[END_REF]. We therefore classified vegetation height into three classes: (i) < 1m, (ii) 1 to 3m and (iii) > 3m. We computed the total area covered by these three classes of vegetation and estimated a fourth variable, i.e., the spatial heterogeneity of the height of the vegetation around each pixel, using the standard deviation of vegetation height. We computed these four variables for the three radii (20 m, 200 m and 500 m radius), resulting in 12 vegetation variables in total. We calculated these 12 variables accounting for all green areas in the All green areas scenario, and repeated this process for the Only public green areas scenario, only accounting for vegetation located in the public green areas (i.e. excluding the vegetation located outside of the public green areas).

Variables describing built areas

Buildings can be a barrier to movement (Hale et al. 2015) but may also be used for roosting [START_REF] Simon | Ecology and conservation of bats in villages and town[END_REF]. Furthermore, intermediate building height has been shown to be linked to higher abundance of insectivorous bird species in Paris [START_REF] Pellissier | Birds are also sensitive to landscape composition and configuration within the city centre[END_REF].

Beyond their direct effects on movement and habitat availability, buildings' height and density can also be considered as a more general indicator of anthropogenic pressure, correlating with light and noise disturbance on an urbanization gradient [START_REF] Grimm | Global change and the ecology of cities[END_REF].

We classified buildings within two height classes. Buildings under 15 m mainly consisted of low-rise buildings and individual houses. This class of building was dominant in the external districts of Paris (Figure 1). Buildings over 15 m were mainly located in the old center of Paris and in the north-west. For each of the three scales detailed earlier (i.e., 20 m, 200 m and 500 m radius), we computed the area covered by the two building classes and attributed the value to the central pixel.

Modeling bat pass abundance using vegetation and built areas

We modeled the relative pass abundance of P. pipistrellus with the previously described vegetation (12 variables) and built areas (six variables), using a boosted regression tree modeling approach (gbm) (gbm package; Greg Ridgeway with contributions from others, 2017) using R 3.4.0 (R Core Development Team, 2018). The gbm approach was relevant in this study because it can handle a large number of predictorseven collinear onesand deal with spatial autocorrelation effectively, and it also has a strong predictive performance (J. Elith, Leathwick, & Hastie, 2008). Because the data contained a lot of zeros (130 points out of a total of 224 points), we employed a Hurdle modeling approach to account for zeroinflation [START_REF] Potts | Comparing species abundance models[END_REF][START_REF] Povak | Machine learning and hurdle models for improving regional predictions of stream water acid neutralizing capacity[END_REF]. This approach is consistent with previous studies modeling bat passes (Aurelie Lacoeuilhe, Machon, Julien, Le Bocq, & Kerbiriou, 2014;[START_REF] Vandevelde | Activity of European common bats along railway verges[END_REF]. The Hurdle model is a two-step modeling approach. The first model, run on data transformed into Presence/Absence pass data, calculates the probability of pass occurrence. The second model is fitted on the pass abundance data (excluding absence data), and aims to predict pass abundance only where bat passes are predicted to potentially occur in the first model. When used for prediction purpose on a new set of environmental data, the Presence/ Absence model is run first. If the predicted value is below a fixed pass occurrence probability (assimilated to predicted absence), the predicted value is maintained.

If the predicted value is above the fixed threshold, then it is the value predicted by the abundance model that is retained. Based on the results of Presence/ Absence modeling, we fixed the threshold between absence and presence at 0.45. Because the number of years of observation varied between the different points, we weighted the points by the number of years of observation. We calibrated the models with a learning rate of 0.0005, an interaction depth of 4 (meaning that we consider interactions), a minimal number of individuals per leaf of 10, and a fraction of 0.6 for training the algorithm (J. Elith et al., 2008). We checked for and did not find any significant residual spatial autocorrelation. As output, the boosted regression tree provides the scaled contribution summing up at 100 (or importance, or influence) of the environmental variables included in the model (Jane Elith, Leathwick, & Hastie, 2008).

Step 2: Evaluating the contribution of private green areas to foragingcommuting habitat availability

Estimating foraging-commuting habitat availability

We used the fitted Hurdle model to predict the bat pass abundances over the entire study area for the Only public green areas and the All green areas scenarios. We then used the resulting bat pass abundance as foraging-commuting habitat availability maps. For the All green areas scenario, predictions were based on the vegetation variables encompassing all green areas, whereas for the Only public green areas scenario, vegetation variables were restricted to the green public areas. We measured total foraging-commuting habitat availability (hereafter referred to simply as habitat availability) for each scenario as the sum of all predicted pass abundance in intramural Paris.

Contribution of private green areas to foraging-commuting habitat availability

We estimated the contribution of private green areas to habitat availability by subtracting the total predicted pass abundance of P. pipistrellus over the entire study area of the Only public green areas scenario from the predicted pass abundance for the All green areas scenario.

Step 3: Evaluating the contribution of private green areas to foragingcommuting habitat connectivity

Conductance maps

Conductance maps depict the ease of movement across the mapped area that varies, for example, with land cover, habitat quality or slope. Conductance maps are used as input data to model connectivity under the Circuit approach. We used the habitat availability maps as conductance maps. This data-based approach is expected to produce more realistic conductance values than would be obtained using expert opinion. We changed the resolution of the two habitat availability maps from 2 m to 20 m by averaging the values of the cells. This change in resolution was needed to be coherent with the bat's perceptual grain, defined as the grain at which an organism responds to the heterogeneity of the landscape [START_REF] Wade | Resistance-surface-based wildlife conservation connectivity modeling: Summary of efforts in the United States and guide for practitioners[END_REF][START_REF] Wiens | Scaling of \textquoterightlandscapes\textquoteright in landscape ecology, or, landscape ecology from a beetle\textquoterights perspective[END_REF]) (see Appendix S3 for details). As P. pipistrellus can only detect its prey within a maximum radius of 3.5 m for small prey and of 15m for large prey [START_REF] Holderied | Echolocation range and wingbeat period match in aerial-hawking bats[END_REF], we consider a resolution of 20 m would adequate fit its perceptual range.We then summed predicted bat passes within all pixels for intramural Paris (excluding the Vincennes and Boulogne parks) to obtain a simple indicator of habitat availability. We obtained the conductance maps by rescaling the predicted pass abundances to values between 0 and 10,000.

Building connectivity maps

We modelled connectivity using Circuitscape, a program that uses circuit theory to model connectivity in heterogeneous landscapes [START_REF] Mcrae | Circuit theory predicts gene flow in plant and animal populations[END_REF]. The Circuit theory approach provides a continuous estimate of connectivity within the area studied, i.e., for each pixel, integrating all possible pathways. We identified two areas, i.e., Boulogne and Vincennes woods, as habitat patches known to house roosts of viable populations of the common pipistrelle and able to act as source for smaller populations within intramural Paris. Furthermore, we know that intramural Paris houses roosts of the common pipistrelle, but their location is unknown. We therefore created and randomly placed a fishnet of points distant of 2 km, each point simulating a possible location of an intramural roost and a potential foraging area. A distance of 2 km corresponds to the higher estimate of the mean distance flight by the common pipistrelle between the roost and the core of the foraging area [START_REF] Nicholls | Contrasting home-range size and spatial partitioning in cryptic and sympatric pipistrelle bats[END_REF]. We added the two woods to these points for a total of roosts / foraging areas. We then simulate the connectivity between pairs of points distant of maximum 2 km (for a total of 38 pairwise connectivity measures), representing that way the connectivity between each roost and foraging areas located at flying distances. Each roost was therefore connected to one to four other points depending on its location in intramural Paris. We used a pairwise modelling mode, meaning that connectivity was assessed accounting for flows coming from and going to each point, meaning that each point was considered acting as roost and as foraging area.

Each node (raster cell) was connected to eight neighbours. For each of the 38 pairwise connectivity measure, Circuitscape provides a connectivity map based on conductance, and a measure of the total conductance between the two points. We obtained a map of connectivity for the entire intramural Paris summing up the 38 connectivity maps to, and estimated the total conductance of intramural Paris summing up the total conductance of the 38 pairwise connectivity measures.

Contribution of private green areas to foraging-commuting habitat connectivity

We estimated the contribution of private green areas to habitat connectivity by subtracting the total conductance value for the Only public green areas scenario from the total conductance value for the All green areas scenario for the entire study area.

Results

Spatial characteristics of public and private green areas in Paris

The total green area belonging to private owners was smaller than the total public green area (36.4% and 63.6 %, respectively; Figure 2a). The private green areas were much more fragmented, as illustrated by a number of patches that was three times higher than for public areas and an average patch size five times smaller (Figure 2b and2c).

Step 1: Modeling and predicting bat pass abundance in Paris

The gbm analyses produced contrasting results for Presence/Absence and abundance of passes data for the built areas and vegetation variables and their scale of impact, suggesting different processes underpinning pass occurrence and abundance (Figure 3, Appendix S4).

The Presence/ Absence of bat passes was dependent on home-range scale (200 m to 500 m radius). The passes were more likely to occur in areas with a high proportion of vegetation and less likely to occur in areas with large concentrations of buildings under 15 m high. The occurrence of bat passes revealed a higher abundance of bat passes when buildings are smaller (under 15 m high), at these scales. The abundance of passes was mainly driven by very local conditions (20 m) and to a lesser extent by home-range scale conditions (200 m and 500 m). Locally, the high proportion of tall buildings was the strongest driver, negatively impacting the bat pass abundance. Overall, the proportion of buildings tended to decrease the abundance of passes at all scales. Conversely, a large proportion of tall vegetation as well as the variation in vegetation height at 20 m and 200 m tended to be beneficial (Figure 3, Appendix S4).

Step 3: Evaluating the contribution of private green areas to foragingcommuting habitat availability

The interpolated predictions of bat pass abundance for the All green areas scenario, showed that larger predicted pass abundances were mainly concentrated in the two large parks of Boulogne and Vincennes (Figure 4) and to a lesser extent within Paris' larger parks.

In intramural Paris, the highest predicted pass abundances were found mostly in the southern and eastern peripheral areas. The map of predicted pass abundances under the Only public green areas scenario also identified the two large parks as main areas of habitat (Figure 4).

The areas with higher predicted habitat availability were the same in the two scenarios, but the predicted abundances were much lower in the No private areas scenario. The predicted pass abundances were extremely low in the dense city center, north of the Seine River.

The total number of predicted bat passes (summed over Paris excluding the woods) was 12,874,960 in the All green areas scenario, and 6,709,623 in the Only public green areas scenario. The difference, i.e., 6,165,337 bat passes, corresponded to the contribution of private green areas to available habitat, and therefore represents 47.9% of the contribution of total green areas to available habitat while private green areas represent just 36.4% of the total green area.

Step 3: Evaluating the contribution of private green areas to foragingcommuting habitat connectivity

The spatial structuring of the conductance maps under the two scenarios revealed close spatial structures with connectivity paths mainly located in the south of Paris (Figure 5). However, the total resistance in intramural Paris was estimated to be 3.55 in the All green areas scenario, compared to 5.59 for the Only public green areas scenario, meaning that private green areas decreased the city's total resistance by 57.6% when compared to the resistance of the Only public green areas scenario.

The connectivity map for the All green areas scenario shows stronger connectivity paths passing through the peripheral areas of the city with the southern area showing higher connectivity levels. In the Only public green areas scenario, the Seine River appeared as the preferred path across Paris, concentrating a large proportion of the flow. The contribution of private green areas to connectivity did not follow clear spatial patterns, either creating new paths or strengthening exiting paths between public green areas, especially in the south (Figure 5).

Discussion

P. Pipistrellus is among the more habitat generalist of bat species [START_REF] Regnery | Tree microhabitats as indicators of bird and bat communities in Mediterranean forests[END_REF] and is regularly found in urban areas [START_REF] Bartonicka | Flight acitvity and habitat use of four bat species in a small town revealed by bat detectors[END_REF][START_REF] Hale | Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large uk conurbation[END_REF][START_REF] Vandevelde | Activity of European common bats along railway verges[END_REF]. In line with previous findings, we observed a positive impact on bat occurrence of the total area covered by vegetation at homerange scales (200 m and 500 m) [START_REF] Azam | Is part-night lighting an effective measure to limit the impacts of artificial lighting on bats?[END_REF]Aurélie Lacoeuilhe, Machon, Julien, & Kerbiriou, 2016). However, while occurrence was more effectively predicted by home-range scale environmental conditions (200m to 500m), bat pass abundance was largely driven by very local conditions (20 m). In other words, while the probability of bat presence was linked to conditions in 200 to 500 m radii, conditions in 20 m to 200 m radii were predominant in explaining the location of the paths. At such very local scales and in line with previous findings, our results showed that higher bat pass abundance is linked to a selection of woody habitats and the avoidance of open habitats [START_REF] Bartonicka | Flight acitvity and habitat use of four bat species in a small town revealed by bat detectors[END_REF][START_REF] Hale | Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large uk conurbation[END_REF][START_REF] Threlfall | Approaches to urban vegetation management and the impacts on urban bird and bat assemblages[END_REF] and to variation in vegetation height [START_REF] Suarez-Rubio | Insectivorous bats respond to vegetation complexity in urban green spaces[END_REF]. The proportion of built areas had a negative overall impact on the presence and abundance of passes although an intermediate proportion of higher buildings appeared to be beneficial for the species [START_REF] Hale | Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large uk conurbation[END_REF]. A similar high building effect has previously been observed in Paris for insectivorous birds, so we may hypothesize that this building structure benefits insectivorous species' foraging activity possibly by concentrating the insects in certain areas [START_REF] Pellissier | Birds are also sensitive to landscape composition and configuration within the city centre[END_REF].

Regarding habitat availability, higher bat activity was recorded and predicted in the peripheral areas of Paris where the higher density of private green areas both enhanced the attractiveness of large public green areas and greatly extended their benefits for the species to the surrounding areas of the city via a net buffering effect. These results highlight the complementary contribution of private and public green areas to habitat availability and quality, a process known as Ecological land-use complementation in research literature [START_REF] Colding | Ecological land-use complementation" for building resilience in urban ecosystems[END_REF]. Here, we observed that large public green areas constitute the main patches of available habitat in the city (core areas) while private green areas increase their capacity to support individuals and enlarge their effective area. Comparable complementation effects of gardens for public areas have been documented elsewhere. While the importance of private green areas for the common pipistrelle has already been demonstrated in previous studies [START_REF] Hale | Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large uk conurbation[END_REF], here we have shown that in Paris private green areas have a disproportionately positive impact on habitat availability vis-à-vis their total coverage. Thus, while private green areas only represented 36.4% of the total green area, we found that they actually supported 47.9% of total habitat availability (i.e. foraging-commuting activity) for the common pipistrelle. This importance could be attributable to the differential types of vegetation favored in private green areas when compared with public green areas. Thus, the areas with high density of private green areas also appear to have higher availability of taller vegetation, which is an important driver of bat activity in our study.

The complementation effect between private and public green areas for the common pipistrelle was even stronger in the case of connectivity, as private green areas decreased the total resistance of the city by 88.7% even though they only represented 36.5% of the total green area. Thus, the spatial configuration of private green areas in the city appeared to be very important for the common pipistrelle, providing the stepping stones between the public green areas that serve as the nodes of the urban network [START_REF] Rudd | Importance of backyard habitat in a comprehensive biodiversity conservation strategy: a connectivity analysis of urban green spaces[END_REF]. If private green areas consist of small patches uniformly distributed across the city, they appear fragmented but not isolated, with the notable exception of the city center which appears highly resistant for the species. A study focusing on the role of green areas at business sites in the Parisian ecological network drew comparable conclusions, enhancing the functional connectivity role of green areas at business sites as stepping stones [START_REF] Serret | Potential contributions of green spaces at business sites to the ecological network in an urban agglomeration: The case of the Ile-de-France region, France[END_REF].

Despite reducing potential connectivity modeling biases using outputs of a model instead of costs for land covers defined by expert opinion, the overall approach we used still has certain limitations. First, as we did not have information about the location of private green areas, we bypassed this problem by only considering public green areas and inferring the importance of private green areas by subtracting the values obtained for the Only public green areas scenario from the All green areas scenario. This method can induce small biases if the delineation of public areas is not perfect, i.e. if the vegetation of the public areas slightly exceeds the shape of the polygons delineating the public green areas. This problem leads at not recognizing those exceeding pixels as being part of the public green areas, while they should be. This translates into an underestimation of the area of public green spaces, while the impact on the location is very little as those pixels are adjacent to the public green areas. It is not possible to quantify the amount or proportion of area concerned by this bias, but it concerns maximum few pixels per public green area. As a consequence, such error is likely to induce a small underestimation of the abundance predicted for the "Only public areas" scenario compared to what would be obtain without this error. Such small variation is expected to have only very small impact on the estimations of the relative importance of public versus private areas for habitat availability and connectivity that could not change the general conclusions of the study. Second, we limited our study area to intramural Paris, excluding the surrounding urban areas where the density of built areas is sometimes lower than in intramural Paris. In other words, we excluded potential connectivity paths linking the two parks but bypassing Paris. The existence of such paths would reduce the flux of individuals flying in/through Paris but would not change the observations concerning habitat availability and connectivity patterns.

Conclusions

This study has two outcomes important for management and conservation strategies in city.

First, it shows the disproportionally high contribution of private green areas to the common pipistrelle habitat availability and connectivity as compared with their total area. Second, it gives support to previous finding on public and private green areas complementary effects.

These findings tend to confirm the benefits of moving towards more inclusive conservation strategies that include both public and private stakeholders in cities [START_REF] Rands | Biodiversity conservation: challenges beyond 2010[END_REF]. Private areas have been found to contain more plant diversity and rarer species than public areas [START_REF] Politi Bertoncini | Local gardening practices shape urban lawn floristic communities[END_REF]. Wildlife-friendly gardening, as time investment in the garden and reducing pesticide, has been shown to positively impact wildlife [START_REF] Goddard | Why garden for wildlife? Social and ecological drivers, motivation and barriers for biodiversity management in residential landscapes[END_REF][START_REF] Muratet | Contrasting impacts of pesticides on butterflies and bumblebees in private gardens in France[END_REF]. Thus, it is the way in which private green areas are managed that could be targeted by new conservation initiatives in cities, following the ones applied to public green areas over the past few years (City of Dublin, 2016;City of London, 2016;Conseil de Paris, 2018;Ville de Paris, 2017). The challenge for conservation is therefore to organize and manage these human-occupied areas to increase their ecological value [START_REF] Dearborn | Motivations for Conserving Urban Biodiversity[END_REF]. This objective for conservation comes with important difficulties linked to the lack of space in cities and changes in owners' needs [START_REF] Warhurst | Front gardens to car parks: Changes in garden permeability and effects on flood regulation[END_REF]. Such changes have for instance led in the past decades to a trend toward gardens' conversion to impervious surfaces, as car parks, clearly antagonistic to conservation objectives [START_REF] Perry | An investigation into the extent and impacts of hard surfacing of domestic gardens in an area of Leeds, United Kingdom[END_REF][START_REF] Warhurst | Front gardens to car parks: Changes in garden permeability and effects on flood regulation[END_REF]).

Figure 1 :

 1 Figure 1: Map of the study area, i.e. intramural Paris. a. shows the location of the bat pass

  Built areas and vegetation data APUR (Agence Parisienne d'URbanisme: Parisian Urban Planning Agency) provided the data on building and vegetation location and height for the year 2012. The data were prepared by APUR based on several orthophoto images with a resolution of 0.5 m that we aggregated to a resolution of 2m. The data and their metadata containing more detailed information about data preparation are freely downloadable from the APUR's website (Atelier Parisien d'Urbanisme, 2014; Atelier

Figure 2 :

 2 Figure 2: Comparison of public and private green areas in the Paris area using three basic

Figure 3 :

 3 Figure 3: Variables ordered by their contribution to the occurrence and bat pass

Figure 4 :

 4 Figure 4: Habitat availability maps of P. pipistrellus in Paris showing the bat pass

Figure 5 :

 5 Figure 5: Conductance maps for P. pipistrellus in Paris representing potential fluxes

757

Nights of recording (in chronological order)

Appendices

Appendix S1: Detailed information on recording settings and conditions 1. Protocol 1.1. General description Table S1-1: Characteristics of the protocol and sampling design used for the monitoring of the temporal trends of bat populations on a national scale by the French Bat Monitoring Programme (Vigie-Chiro, 2018), supervised by the French Museum of Natural History. In brackets and bold are indicated the small adaptations of the protocol made for the data used in the present study.

Bat activity records

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 together with Scan'R (Binary Acoustic Technology, 2010) to isolate each bat vocalization and automate measurement 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], Barataud 2012) and even less in continuous urban fabric context such as Paris where species overlapping on acoustic repertoires (such as P. pygmaeus or Miniopterus scherbersii) do no occur.

Measurement of bat activity

Bat activity at the point scale is calculated as the sum of the number of bat passes recorded per 6 minutes (Fig S1 -2a). We identified a bat pass as a call sequence containing one or more pulses and when the time between calls exceeded four times the inter-pulse interval [START_REF] Parsons | Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks[END_REF][START_REF] Kerbiriou | Potential of bat pass duration measures for studies of bat activity[END_REF]). In the protocol followed in this study, the duration of the record is fixed at 1.2 seconde. Within each 1.2 s recording, the minimum number of bat recorded simultaneously were estimate using inter-pulse interval and frequency (Fig S1 -2b).

Exploring potential biases

Patterns of nightly activity of P. pipistrellus

Volunteers are strongly encouraged to conduct their sampling during daily peak activity [START_REF] Roche | Development of a car-based bat monitoring protocol for the republic of Ireland[END_REF], i.e. beginning thirty minutes after dusk (FBMP recommendations). It usually takes less than 3 hours to sample the 10 recording points of each square: 97% of data collected in Paris occurred between 30 minutes and 3h30 after sunset. During this period the pattern of nightly activity in urban context for P. pipistrellus is relatively flat (Fig. S1-4) To protect from Type I error, a Bonferroni correction should be considered: for an alphavalue (α original =0.05) the Bonferroni correction (α adjusted = α original /k ; α adjusted =0.0028), thus to determine if any of the 18 correlations is statistically significant, the P-value must be P<0.0028 500) Shrub ( 20) Shrub ( 200) Shrub ( 500) Herbaceous ( 20) Herbaceous ( 200) Herbaceous ( 500

Correlation between time of recording and the set of explanatory variables

3.3.Variation of explanatory variables among recording's nights

Appendix S3

Too small a resolution would result in increasing the resistance of the matrix by allowing very small elements (in this case 2m) to counter the movement, while the individual could in reality bypass the element.

We chose to aggregate data at this step, and not earlier in the analyses, mainly because the private green areas are usually small areas and would have disappeared with the degradation of the vegetation raster, resulting in an extensive loss of primary information for the object being studied. When tackled at this stage, the problem is much less important because we are dealing with continuous data that are simply averaged at the coarser resolution.


Philippe Fontanilles
email: fontanilles.oiso@laposte.net

Iván De

La Hera

Kevin Sourdrille

Florent Lacoste

Iván De La Hera

Christian Kerbiriou

F Esnault

S Valles

L Delalande

F Delfour

A Glad

Stopover ecology of autumn-migrating Bluethroats (Luscinia svecica) in a highly anthropogenic river basin

Keywords: Luscinia svecica, home range, body condition, habitat selection, corn crop, diet, trophic resources

come   L'archive ouverte pluridisciplinaire

Introduction

The global conservation of migratory birds not only relies on the protection of their breeding and wintering habitats, but also on the presence of suitable stopover sites along their migratory routes [START_REF] Hutto | On the importance of en route periods to the conservation of migratory landbirds[END_REF], Young 2000[START_REF] Newton | The migration ecology of birds[END_REF]). Coastal marshes, estuaries and other types of wetlands are highly productive habitats largely used during migration by waterbirds and other avian species, constituting key conservation areas [START_REF] Czech | Agricultural Wetlands and Waterbirds: A Review Author(s): Waterbirds: The International Journal of Waterbird Biology[END_REF]. Wetland habitats experienced a dramatic reduction and an increased fragmentation during the 20th century, mainly as a consequence of the pressure of human activities, such as urbanization and the drainage for agricultural use [START_REF] Von Behren | Impact of agriculture and urban development on the community structure of wetland birds in East Central Minnesota[END_REF][START_REF] Whited | The importance of local and regional factors in predicting effective conservation Planning strategies for wetland bird communities in agricultural and urban landscapes[END_REF][START_REF] Czech | Agricultural Wetlands and Waterbirds: A Review Author(s): Waterbirds: The International Journal of Waterbird Biology[END_REF]. As a result, wetlands usually remain now embedded in a complex and highly-altered human matrix, where every year migrating birds rest and search for food to undertake their next flight bout. The wetland remnants that many birds use as stopover sites are normally small and face some common problems that, in some cases, can be mitigated by human intervention. For example, many wetland managers implement measurements to avoid clogging, which could lead to bush encroachment and the progressive disappearance of marsh vegetation (Clark and Wilson 2001); while the control of invasive and exotic species, that can alter wetland biodiversity and functioning, is also a common practice [START_REF] Fontanilles | Sélection des habitats et occupation spatiale du Phragmite aquatique Acrocephalus paludicola sur une halte migratoire du sud-ouest de la France, mise en place d'une gestion intégrée[END_REF][START_REF] Arizaga | Spatial behaviour and habitat use of first-year Bluethroats Luscinia svecica stopping over at coastal marshes during the autumn migration period[END_REF]). These measurements would increase the quality and carrying capacity of the wetlands, which would be very beneficial for migrating birds (e.g. fuel acquisition; [START_REF] Delingat | Habitat utilization by Northern Wheatears (Oenanthe oenanthe) stopping over on an offshore island during migration[END_REF]. Another aspect that has hitherto received little attention is the potential management and planning of the areas surrounding the wetland. These adjacent areas might be intensively used by migrants given the restricted size of wetland patches and the potential high intra and interspecifc competition with other migratory and resident individual birds. This situation could be particularly exacerbated during the migration peaks, when large number of individuals can meet together in a single location [START_REF] Peris | Population limitation in migrants[END_REF]. Such circumstance predicts that many migrants will be forced to expand their home-ranges and use alternative habitats out of the wetland. In this context, identifying which alternative habitats are positively selected by migrating birds during their brief stopovers would be essential to design buffer areas that best meet the requirements for these en route migrants. However, our knowledge of the stopover ecology and behaviour of migratory birds is still very limited. In this study, we analysed the stopover ecology of migrating Bluethroats Luscinia svecica in Barthes de la Nive (France) during autumn migration. Barthes de la Nive is a mosaic of wetlands, riparian woodlands and farmlands located near the Adour River mouth in the Southwestern Atlantic coast of France. The scattered wetlands in this region attract a large diversity of both aquatic and non-aquatic birds during migration periods (Fontanilles et al. 2011). The only radiotracking study carried out in this area so far showed that the globally endangered Aquatic Warbler Acrocephalus paludicola had a strong preference for reedbeds but, to a lesser extent, it also made use of some farmlands [START_REF] Fontanilles | Sélection des habitats et occupation spatiale du Phragmite aquatique Acrocephalus paludicola sur une halte migratoire du sud-ouest de la France, mise en place d'une gestion intégrée[END_REF]. This highlights the relevance that the surrounding matrix might have even for a wetland specialist as the Aquatic warbler. Conversely, Bluethroats are migratory birds that can use a large range of habitats, mainly reedbeds and marshlands [START_REF] Arizaga | Do subspecies of bluethroat Luscinia svecica show a geographic segregation during the autumn migration period in Spain?[END_REF][START_REF] Musseau | Importance of intertidal wetlands for the French coastal endemic Bluethroat (Cyanecula svecica namnetum) and conservation implications in the context of global changes[END_REF]), but also bushlands, woodland and farming habitats [START_REF] Cramp | The Birds of the Western Palearctic[END_REF][START_REF] Th | Extension géographique et écologique de la Gorgebleue à miroir Luscinia svecica dans le Centre-Ouest de la France[END_REF]Chiron, 2017, Berndt andHölzl 2012), making it an interesting model to study its stopover ecology and habitat selection during migration. [START_REF] Arizaga | A comparison of stopover behavior of two subspecies of the Bluethroat (Luscinia svecica) in Northern Iberia during the autumn migration period[END_REF] radiotracked 20 autumn-migrating Bluethroats in Txingudi (North Spain), a wetland located less than 30km away from Barthes de la Nive. Their results showed a strong selection for reedbeds, lowhalophytic vegetation and tidal flats. However, Txingudi is located in a more urbanized environment that probably greatly restricts bird movements, and its proximity to the river mouth allows the presence of habitats that are lacking in Barthes de la Nive (e.g. halophytic vegetation). On the other hand, bird ringing information obtained for both wetlands during autumn migration showed dramatic differences in the number of selfrecoveries, which are much more usual in Txingudi than in Barthes de la Nive [START_REF] Arizaga | A comparison of stopover behavior of two subspecies of the Bluethroat (Luscinia svecica) in Northern Iberia during the autumn migration period[END_REF]Fontanilles unpublished data). These differences could be a consequence of a longer stopover duration of Bluethroats in Txingudi than in Barthes de la Nive, but they could also be caused by the existence of larger home ranges in Barthes de la Nive, something that would be possible in its much less urbanized surrounding. All these aspects suggest a different stopover ecology and behaviour of Bluethroats between both wetlands in spite of their geographic proximity that remains still unexplored. In order to better understand the stopover ecology of the Bluethroat in Barthes de la Nive, we performed a radiotracking study during autumn migration that aims to shed light on (1) the stopover duration and the proximate factors that affect it, (2) habitat selection and home range sizes, and (3) we complemented the study with an analysis of Bluethroat diet and the availability of food resources. Although Bluethroats are not globally threatened, some populations have been considered to be under high risk of extinction (Huntley et al. 2007). Consequently, we expect that the spatial information generated in this study could be valuable for the competent authorities to design management practices out of the wetlands patches that could contribute to the conservation of Bluethroats and other birds during their migrations. MATERIALS AND METHODS Study area and vegetation map Barthes de la Nive (43°27'N; 01°28'W) is a 442-ha mosaic of natural and anthropogenic habitats (Fig. A1), whose remaining wetlands have been maintained safe from complete drainage due to its role in reducing the risk of flooding in Bayonne city. The wetlands are connected to the Adour river by channels, so that its hydrology is influenced by the flow of the river and the tidal regimes. However, its natural influence and ecologic functions in Adour estuary were drastically affected to urbanize the city, to develop port facilities and dykes, which virtually destroyed the original mudflats and intertidal areas. Our study site is now a protected area included in the European Natura 2000 network (FR7200786). The non-urban areas near the river have been widely used for pasture, as hay meadows and other agricultural purposes, being corn plantations the primary crop nowadays. Farming in the region uses a reasonably low quantity of fertilizers and no use of insecticides. Field abandonment and lack of management is increasing gradually bush and tree encroachment, which is changing dramatically the landscape. A vegetation map was obtained from photo-interpretation and field validation for summer 2014 and 2015 (Fig. A1,Table1). This approach showed the relative importance of each habitat in the region (see Table 1).

Bluethroat trapping and body measurements

Mist-netting sessions were performed from mid-August to late September when migrating Bluethroats stopover in this region during their post-breeding migratory period. Note that Bluethroats do not breed in Barthes de la Nive or use it for moulting (Fontanilles et al. 2011). Ringing sessions took place in five different locations across the study area: four wetlands and one corn crop (see details in Supplementary Material Fig. A1,Ap. 3,Table 2). These five sites were reasonably distant each other to reduce potential geographic bias and, according to previous studies (Fontanilles et al. 2011[START_REF] Fontanilles | Migration et régime alimentaire de la Gorgebleue à miroir dans les Barthes de l'Adour, Actes du séminaire "Conservation des espèces et gestion des zones humides[END_REF], they represent the two main habitats (i.e. reedbed, corn crops) where Bluethroats occur during their stopover at Barthes de la Nive.

To maximize the number of captures, we used one male song playback from 30 minutes before dawn (when mist-nets were open) until a tagged bird was released (when mist-nets were furled). By using the tape lures only 30 minutes before sunrise, we reduced the possibilities of forcing the landing of migrating Bluethroats and we expected to capture only birds that decided voluntarily to stop over in our study area [START_REF] Schaub | Does tape-luring of migrating Eurasian Reed-Warblers increase number of recruits or capture probability?[END_REF][START_REF] Arizaga | Biases associated with the use of a playback in stopover ecology studies in small passerine birds[END_REF]. During our ringing sessions, we captured 58 Bluethroats (28 in 2014 and30 in 2015). Several morphological measurements were taken from each bird in order to obtain a composite index of bird body size [START_REF] Freeman | Univariate metrics are not adequate to measure avian body size[END_REF]Jackson 1990, Tellería et al. 2013, see Supplementary Material). We also recorded body mass (±0.1 g) and standard scores of fat and muscle [START_REF] Busse | Bird Station Manuel. SE European Bird Migration Network[END_REF]. Body size-corrected measurements of body mass were used to estimate the relative quantity of body reserves carried by each Bluethroat. This was done using linear regression of body mass on body size (see Supplementary Material Ap. 2, Fig. A2), where individuals with more body reserves showed more positive residuals [START_REF] Salewski | Estimating fat and protein fuel from fat and muscle scores in passerines[END_REF].

Radio tracking information

Out of the 58 Bluethroats captured, 29 juveniles were equipped with a radio-transmitter, with a minimum of 4 radiotagged individuals in each of the 5 ringing sites (25 birds were trapped in the reedbeds and 4 in the corn crops; see details in Supplementary Material, Ap. 3, Table A2). Life expectancy of the emitters is typically more than 17 days and the average detection distance is 80-300 meters. We only tagged first-year birds because the study site is mainly used by first-year birds; and because juveniles face their first autumn migration and, consequently, their habitat choice cannot be influenced by previous experience [START_REF] Piper | Making habitat selection more "familiar": a review[END_REF]. On the day of capture, monitoring of tagged Bluethroats started at least one hour after the bird was released in order to avoid bias linked to potential stress behaviour. For birds that stayed in the area the following days after capture (see below), they were normally monitored 8h per day during, normally, 3-4 days in long-staying individuals. After this period, we checked the presence every day, but the intensity of the radiotracking typically got reduced and depended on other duties associated with the project, particularly, the trapping and monitoring of other individuals (see Supplementary Material Ap.3 for more details). The positions of the birds were obtained normally by triangulation (3 vectors taken consecutively within less than 10 minutes), but we used bi-angulation in those cases in which landscape barriers (like canals, rivers or dense vegetation) impeded taking more than two informative vectors, or just one vector plus an estimation of the actual distance to the bird when this was observed. We used Sika receivers (Biotrack Ltd) and Yagi antennas to find the birds, and vectors were delimited using a GPS (to determine observer position) and a compass (to obtain magnetic Azimuth). All this information was computerized using the software Cartoexploreur, and we considered the centroid of the triangle determined by the three corresponding vectors as the most likely geographic position of the bird, or the intersections between lines when two vectors were only available. Prior to the start of radiotracking, observers were trained in the study area and the accuracy of the triangulation method was assessed. The average error found in the estimation of the positions of transmitters hidden in the study area was 14.5±1 se m (n=69), which can be considered enough given the purpose of studying main habitat selection. Stopover duration and its determinants We used the number of days spent by each Bluethroat after being tagged (assessed by the radiotracking survey) as a proxy of stopover duration. This approach is expected to provide a better idea than ringing recaptures on how long Bluethroats stopover in Barthes de la Nive, since ring-recovery data are spatially restricted, have a lower detection probability and strongly depend on a good sampling strategy (Chernetsov 2012). According to the non-Gaussian distribution of stopover durations (see Fig. A3) we performed non parametric tests (Wilcoxon tests, Kruskal-Wallis tests and Spearman correlations) to evaluate which factors (year, sex, site, date of capture, muscle development, fat accumulation and body condition) better correlated with the observed variation in the length of the stay of Bluethroats.

Habitat selection

Initially, we tested whether Bluethroat locations were randomly distributed among habitats. We applied the quadrats method (Zaminetti 2005) by defining a grid of K squares 100 x 100 m enveloping all the radio-tracking points. The theoretical distribution K th (n) was obtained following the Poisson's law:

K nth = [K*(D n /n!)]*exp(-D)
where n is the number of points per mesh, K(n) the number of stitches having n points, N is the total number of locations and D is the average density of locations by cell that is defined as N divided by K. The existence of significant differences between the two distributions (i.e. K (n) and K th (n)) was assessed using a Kolmogorov-Smirnov test. Secondly, for assessing habitat selection, we calculated for each habitat the electivity index of [START_REF] Jacobs | Quantitative measurement of food selection: a modification of the forage ratio and Ivlevs' selectivity index[END_REF]

I h = U -D / (U + D -2U*D)
where U is the proportion of locations in habitat h and D the proportion of this habitat in the study area. The index ranges between -1 (strong rejection of a particular habitat) and 1 (strong selection). We used the proportion of locations instead of the proportion of areas in core areas to take into account the edge effects and to be more precise with the actual habitat used. We excluded habitats poorly represented showing less than 5 locations.

Home range estimates

The overall home range size of each individual Bluethroat was estimated by the model of 95% kernel (K95; [START_REF] Worton | Kernel methods for estimating the utilisation distribution in home range studies[END_REF]). The K95 approach is usually used in this type of studies, which would allow between study comparisons [START_REF] Börger | Effects of sampling regime on the mean and variance of home range size estimates[END_REF]. Areas of high occupancy were also estimated using the 50% kernel (K50), considered as a good estimator of core areas [START_REF] Börger | Effects of sampling regime on the mean and variance of home range size estimates[END_REF]. We calculated the overall home range with all the locations for each bird and also for each day when there was a minimum of 10 positions. Home range sizes were processed using the Ranges 8v2.10 software (Anatrack ltd).

Home range analysis

We explored whether overall home range size varied in relation to the proportion of habitats contained within it (10 habitat variables, see Table 1), several metrics of heterogeneity (mean patch size, number of habitat or Shanon index perform of patch size distribution) and individual-associated variables (body condition, sex and stopover duration). For that purpose, we performed General Linear Models (GLM) using the home range size (50% kernel and 95% kernel) as a response variable, while habitat cover and individual-associated variables were included as explanatory variables. According to the distribution of home range size (positive long tail distribution), we applied a negative binomial error distribution to the GLM in order to minimize issues related to the over-dispersion ratio in the models (i.e. as close as possible to 1; Zuur et al. 2009). Following a multi model inference [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[END_REF]), we generated a set of candidate models containing all possible variable combinations and ranked them by corrected Akaike information criterion (AICc) using the dredge function (R package MuMIn). We only integrated the models complying with the following conditions: (i) models do not include simultaneously correlated covariates (R² > 0.7) and (ii) models do not include more than three variables to avoid over-parameterization due to the limited data set. Since the simultaneous inclusion of habitat cover and measures of habitat heterogeneity generated important multi-collinearity problems, we decided to perform two separate modelling: one with habitat cover within the home range and individualassociated variables; and a second one, with measures of habitat heterogeneity and individual-associated variables (results of this second modelling are shown in Appendix 5). We restricted this set of models using a cut-off of 2 AICc. The modelling with habitat cover resulted in 4 and 3 top models for 50% Kernel and 95% Kernel, respectively (see Supplementary Material Ap. 5, Table A3). The modelling with measures of habitat heterogeneity resulted in 4 and 2 top models for 50% Kernel and 95% Kernel, respectively (see Supplementary Material Ap. 5). Following the same approach, we explored whether daily home range size (with a minimum of 10 positions) varied in relation to habitat cover within home range, individual-associated variables. According to the hierarchical structure of this data set (radio-tagged individuals survey each day), we treated the variable "individual identity" as a random effect, while considering the other explanatory variables (home range and individual-associated variables) as fixed effects (Zuur et al. 2009). Following a multi model inference using General Linear Mixed Models with a negative binomial error distribution, the daily home range analyses resulted in a total of 2 and 3 top models for the 50% and 95% kernel, respectively (see Supplementary Material Ap. 5, Table A). We also used a secondary method based on PCA analysis detailed in Supplementary Material Ap. 6. Roosting habitat selection To provide information on roosting behaviour, we identified the habitats used between sunset and sunrise (roosting locations) and also estimated their distance to the daytime, potential, foraging areas. We identified the habitat of all those locations on the vegetation map. We compared the proportions of roosting locations occurring in each habitat to identify the most used by a posteriori Wilcoxon test. For birds flying to a roosting location far away from the area used during daytime hours, we calculated the distance between the centroid of the home range exploited during daytime hours and the core of roosting locations. We then compared the proportions of habitats between these two areas (home range during daytime hours vs. roosting locations core) by a posteriori Wilcoxon test.

Diet of Bluethroat

To try to elucidate why birds tend to select specific habitats, we analysed their diet and the invertebrate availability. We collected 105 faecal samples during ringing operations for all sites in 2015 (n=52) and 2014 (n=30) and only in Urdains in 2012 (n=23). All remains identified in faeces were used to estimate the minimum number of prey items and the occurrence of each taxonomic group within each sample. While some bias in diet analyses was possible because small or soft-bodied preys are less easily detected, strong correlation has been found between prey remains in droppings and the actual composition of the diet (Davies 1977a(Davies , 1977b)). We also assessed prey biomass using predictive models based on the relationship between body length and mass of terrestrial arthropods (Hodar 1996; see Supplementary Material Ap. 7 for additional details). We explored which factors influenced the prey abundance, testing explicitly the effects of age (young vs adult birds), sex and day using a Generalized Linear Model (GLM) with a Poisson error distribution. P-values were corrected for overdispersion. Only taxa representing more than 2% of the prey abundance were considered

Invertebrate availability between habitats

We estimated the variation in the abundance of (near) ground invertebrates (the main feeding substrate of Bluethroats) between the two main habitats occupied by Bluethroats (corn crops and reedbeds). Given the large extension of the study area, we decided to focus our invertebrate sampling on three of the five trapping areas: the corn crop area, and Villefranque and Urdains reedbeds (Fig. A1). The corn crops in the other bank of the Nive River had similar plantation and exploitation, so we assumed them to have a similar invertebrate availability. We used 3 standardized coloured (yellow, white, blue) bowl traps and a pitfall glass per station (for a total of 12 stations, 6 in the corn crops, 3 in each reedbed). All stations were sampled simultaneously at 3 temporal stages in August 2015. Traps were deployed for four days. For more details, see Supplementary Material Ap. 8. For subsequent analyses, we pooled together the data of the three bowl traps of each station. We focused the analyses on those taxa whose remains had been found in faeces of trapped Bluethroats. We compared invertebrate availability, abundance and biomass between the two reedbeds and the corn crop using General Linear Models with a Poisson error distribution. Unless specified, mean values are given ± se (standard error).

RESULTS

Stopover duration and body condition effect

Tagged Bluethroats stayed 5 days (±1se; range 1-20) on average upon capture in Barthes de la Nive, but showing a clearly non-Gaussian distribution where up to 13 individuals left the study area the next night after being captured (Fig. A3). The remaining 16 Bluethroats stayed on average 8.4 ± 1.3 days (see Table A1, Fig. A3). Observed variation in stopover duration did not differ significantly between years (W=91, p=0.536), sites (Kruskal-Wallis H(3, 29) =1.11, p=0.774), sex (W=133, p=0.189), date of capture (r Spearman= -0.11, t 27 = -0.59, p=0.558) or muscle development (r Spearman= -0.17, t 27 = -0.92, p=0.365). The fat score was significantly associated with stopover duration (r Spearman= -0.40, t 27 = -2.24, p=0.034). However, the individual trait that better explained stopover duration was the quantity of body reserves, which was estimated from the residuals of body mass on body size (effects of body size on body mass: β=0.888, F 1,27 =100.9, p < 0.001). Thus, Bluethroats with relatively more body reserves for a given body size left the Nive basin earlier on average (r Spearman= -0.59, t 27 = -3.78, p< 0.001; Fig. 1) than birds with relatively less body reserves. Additionally, we analysed whether stopover duration differed between habitats used. Irrespective of where they were trapped, birds that used corn crops during their stay remained significantly (W=23, p<0.001) longer (10 days ±1.1se, n=10) in the area than those not using this habitat type (2.7days ±0.6se, n=19; see Fig. 2). .

Habitats selection

The 29 radiotracked juvenile Bluethroats provided 1718 positions during their stay in our study site. Bluethroat locations were not randomly distributed among habitats. Their distributions differed significantly from the theoretical null distributions (Kolmogorov-Smirnov test D = 0.896, p <0.0001). The main habitats used by all birds were corn crops and reedbeds, either pure or mixed (Fig. 3). The distribution differed between birds staying one day, which preferred pure reedbed (W=55.5, p=0.034), and the rest, which positively selected the corn crops (W=162, p=0.013). The birds stopping over for just one day made use of less habitat types (2.2± 0.3 [1-4] habitats) than birds staying longer (4.7± 0.5 [2-10]; W=180.5, p<0.001). However, during the first day of stay, there were no differences between them in the preferred habitat and number of them (tests Wilcoxon, p> 0.05, Fig. A4). Regarding the available habitats (Fig. 4), Bluethroats strongly positively selected pure and mixed reedbeds, corn crops and hydrophilous tall grasslands. They moderately selected paths, wooded reedbeds and mesophic grasslands, while they avoided water, railways, ferns, wet grasslands, houses, woodlands and hay meadows.

Home range analysis

The average number of locations per individual was 59.2 ± 9 (22.5 ± 1.6 for birds staying one day, and 89 ± 12 for birds staying longer). The average overall K95 home range was 5.8 ± 1.8 ha with a large variation between individuals (standard deviation 9.9, range 0.016-46.5). The core area (i.e. K50) was on average 1.36 ± 0.35 ha (standard deviation 1.87, range 0.004-7.6). K95 areas were larger in birds staying more than one day (9.72 ± 3 ha) than in birds stopping over just one day (1.07 ± 0.46 ha; W = 23, p< 0.001). Similar results were obtained for the K50 core area: 0.28 ± 0.12 ha for long-staying birds, and 2.24± 0.53 ha for birds staying only 1 day (W = 18, p< 0.001). Bluethroats with greater overall home range included more wet grassland, woodland and mesophilic grassland within their range, and also exhibited longer stopover duration. On the other hand, Bluethroats with smaller overall home range exhibited larger quantities of body reserves and occupied areas with a higher proportion of reedbed (Table 2). Analyses performed for daily home ranges highlighted that Bluethroats with greater home range included more hay grasslands, open water, and woodlands; while Bluethroat with smaller daily home range occupied areas with a higher proportion of crop fields, natural paths and pure reedbeds (Table 2). In addition, analyses performed with measures of habitat heterogeneity, showed that Bluethroats with greater overall home range exhibited a more diversified home range (Appendix 5). According to AICc, measures of habitat heterogeneity performed better than habitat cover variables for K95, while the opposite was true for K50 (Appendix 5). A second analytical method based on PCA analysis gave similar results (see Supplementary Material Ap. 6).

Roosting habitat selection

We identified the overnight habitat in 26 Bluethroats. Pure reedbed was the main roosting habitat, with 44.2% of the nights (Fig. 5). Mixed or wooded reedbeds were also well-represented within the roosting habitats, representing 17.5% and 16.8 %, respectively. So, reedbeds (pure, mixed and wood reedbed) were the preferred habitats for roosting (80.1± 8% of nights) in 23 birds that stayed for at least one night. Corn crops were also used by 5 birds but less frequently than reedbeds: 13.1 ± 6% of nights. 83% of birds spending the night in reedbeds (pure, mixed and wood reedbed) occupied the same reedbed during the day. This took place in 59 ± 9 % of the nights (Fig. 6). This particularly concerned the 13 Bluethroats which stopped for one day. Individuals staying for at least 2 days showed relatively predictable movements and selected repeatedly the same areas during the night. 27% of the birds (7) spent overnight in a reedbed (Urdains or Villefranque) and normally moved during the day to a corn crop. This was noticed for 12.5 ± 5 % of the nights. We calculated the distance between roosting core areas and daytime foraging core areas. Birds flew on average 397 ± 33 m to reach its roosting location (n=10, range 80-692 m). Five birds also used corn crops to stay during the night after using it also during the daytime (19 nights).

Diet analyses and available invertebrates within habitats

We analysed Bluethroat diet and invertebrate availability to explore foraging preferences. We obtained 105 faecal samples: 84 faecal samples from first year birds and 21 from adults, 55 from males and 47 from females. A total of 431 prey items were identified, 4.1 ± 0.8 on average per dropping. We found 14 orders of invertebrates (2.2 ± 0.3 on average per sample). The diet of Bluethroats was dominated by ants Hymenoptera Formicidae, representing 45.5 % of preys and occurring in 54% of the samples (Table 3). Araneidae was the second most abundant group (20.4%) with a similar occurrence to ants (53%); and Coleoptera was the third most common group (10.2% of all preys and 31% of the samples). These two last taxa were the main contributors to the consumed biomass, representing 64.7 % and 14.9%, respectively. We did not detect any significant effects of Bluethroat age and sex on prey abundance. We did also observe that Cicadellidae was less consumed over time (Table 3). Corn crops hosted significantly more invertebrates and biomass than reedbeds for Coleoptera, Diptera and Araneida in pitfalls, and for Cicadellidae in bowls (Table 4). Corn crops also had higher availability of not-Formicidae Hymenoptera than Urdains in bowls, but less than Villefranque. Finally, Formicidae was more abundant in Urdains than in the other two sites.

DISCUSSION

Variation in stopover duration and home range size Bluethroats showed large individual variation in their stopover duration and home range size in Barthes de la Nive. Observed mean values differed from those obtained by [START_REF] Arizaga | Spatial behaviour and habitat use of first-year Bluethroats Luscinia svecica stopping over at coastal marshes during the autumn migration period[END_REF]. Thus, stopover duration was shorter and home range larger in Barthes de la Nive (mean stopover duration of 5 days and mean home range size of 5.8 ha) than in Txingudi (9.6 days and 2 ha, respectively). Differences in stopover duration between these two sites were mediated by the fact that 45% of the radiotracked Bluethroats in Barthes de la Nive apparently departed the following night after capture, a circumstance that never took place in Txingudi (Fig. A3).). If these short-staying individuals were excluded from the calculations, the stopover duration in Barthes de la Nive (i.e. 8.4 days) would conform better to the values obtained in Txingudi. After the signal of a bird disappeared from the place it was last detected, we carefully explored the whole study area by car the following day in its search, and sporadically the following days. This makes us very confident that the stopover duration estimates obtained in Barthes de la Nive are reliable. Likewise, the fact that only one of the 29 radiotracked Bluethroats stayed longer than the life-expectancy of the transmitter would not alter these between-site differences or the general conclusions of our study (see below). Actually supporting the longer stopover duration of Bluethroats in Txingudi, it was slightly higher (3 out of 20) the number of Bluethroats whose stay reached the expected functional life of the transmitters in this wetland than in Barthes de la Nive. It could be argued that the higher number of short-staying Bluethroats in Barthes de la Nive was caused by the use of playbacks during the trapping sessions, which were not implemented in Txingudi. However, current evidence would not support this hypothesis, since the use of playbacks typically attracts Bluethroats with lower body reserves [START_REF] Arizaga | Biases associated with the use of a playback in stopover ecology studies in small passerine birds[END_REF] and, as our results show, birds with less fuel loads would tend to have longer stopover durations [START_REF] Alerstam | Optimal bird migration: the relative importance of time, energy and safety[END_REF][START_REF] Salewski | Stopover duration of Palearctic passerine migrants in the Western Sahara; independent of fat stores?[END_REF]. This bias of playback use on the body reserve loads of autumn migrating Bluethroats was consistent in the three wetlands (on the Bay of Biscay, Gironde, Txingudi, Urdaibai) analysed by [START_REF] Arizaga | Biases associated with the use of a playback in stopover ecology studies in small passerine birds[END_REF] that are geographically close to Barthes de la Nive. If Bluethroats do show transient vs. non-transient divergent behaviours during migration as have been described for other migratory species [START_REF] Rappole | Relationships between behavior, physiology and weather in avian transients at a migration stopover site[END_REF], playbacks might have also biased stopover duration estimates if they do preferentially attract transient individuals. Again, the results obtained by [START_REF] Arizaga | Biases associated with the use of a playback in stopover ecology studies in small passerine birds[END_REF] do not support this possibility, since playbacks do not seem to affect the number of Bluethroat recaptures, and this would be an expected outcome if playbacks promoted the capture of more transient individuals that will have less recapture prospects. Likewise and contrary to what would be expected for their transient condition, these short-staying individuals did not move as much as would be expected after being trapped in Barthes de la Nive, and their first-day home range did not differ significantly from that observed for long-staying conspecifics. ). Additionally, overall home ranges are nearly twice to three times larger in Barthes de la Nive than in Txingudi [START_REF] Arizaga | Spatial behaviour and habitat use of first-year Bluethroats Luscinia svecica stopping over at coastal marshes during the autumn migration period[END_REF]. [START_REF] Musseau | Importance of intertidal wetlands for the French coastal endemic Bluethroat (Cyanecula svecica namnetum) and conservation implications in the context of global changes[END_REF] also found home ranges of similar size to [START_REF] Arizaga | Spatial behaviour and habitat use of first-year Bluethroats Luscinia svecica stopping over at coastal marshes during the autumn migration period[END_REF] in moulting Bluethroats.). These contrasting differences between Txingudi and Barthes de la Nive are very likely mediated by the strong differences in the degree of urbanization and habitat composition that seem to have profound consequences in the stopover behaviour of Bluethroats between two relatively close locations.

Habitat and roosting site selection

Migrating Bluethroats in Barthes de la Nive strongly selected reedbeds (pure and mixed) and other hydrophilic natural grasslands, which concurs with the favourite habitat that [START_REF] Arizaga | Spatial behaviour and habitat use of first-year Bluethroats Luscinia svecica stopping over at coastal marshes during the autumn migration period[END_REF] and [START_REF] Musseau | Importance of intertidal wetlands for the French coastal endemic Bluethroat (Cyanecula svecica namnetum) and conservation implications in the context of global changes[END_REF] found for migrating and moulting conspecifics, respectively. Much less known was the preference of migrating Bluethroats for corn crops, although one study had detected this species in this crop type during migration [START_REF] Gottschalk | Migratory and visiting birds in a maize field near Giessen, Germany in summer and autumn[END_REF] and some populations of Bluethroats seem to thrive and even breed successfully in some agricultural fields, such as oilseed rape crops [START_REF] Th | Extension géographique et écologique de la Gorgebleue à miroir Luscinia svecica dans le Centre-Ouest de la France[END_REF][START_REF] Berndt | Energy crops as a new bird habitat utilization of oilseed rape fields by the rare Bluethroat (Luscinia svecica)[END_REF]Hölzl 2012, Chiron 2017). We did not find the preference of Bluethroats for tidal mudflats or low-halophytic vegetation described in other studies [START_REF] Arizaga | Spatial behaviour and habitat use of first-year Bluethroats Luscinia svecica stopping over at coastal marshes during the autumn migration period[END_REF][START_REF] Godet | Bluethroats Luscinia svecica namnetum offset landscape constraints by expanding their home range[END_REF][START_REF] Musseau | Importance of intertidal wetlands for the French coastal endemic Bluethroat (Cyanecula svecica namnetum) and conservation implications in the context of global changes[END_REF], but the representation of these habitats in Barthes de la Nive is relatively limited, which could explain this lack of use. Our results showed that home-range size is smaller when birds occupied reedbeds (for overall home ranges) and corn crops (for daily home ranges). A potential explanation for this result is that these habitats might offer more trophic resources, which would prevent birds from moving long distances in search for food [START_REF] Bibby | Foraging behaviour of migrant pied flycatchers, Ficedula hypoleuca, on temporary territories[END_REF][START_REF] Chernetsov | Contrasting spatial behaviour of two long-distance passerine migrants at spring stopovers[END_REF]). Another complementary hypothesis for the higher occurrence of Bluethroats in these two habitat is that, given their dense structure, they could also provide a suitable shelter, not only for roosting during the night but also to rest during daytime between migration flight bouts. The use of reedbeds as roosting habitat has been described before in Bluethroats [START_REF] Eybert | La Gorgebleue[END_REF][START_REF] Harmange | Unexpected movements of male Bluethroats Luscinia svecica namnetum during the breeding period] Déplacements inattendus chez des mâles de Gorgebleue à miroir blanc Luscinia svecica namnetum en période de nidification[END_REF]) and our study confirmed this preference and suggested that corn crops might occasionally play a similar role. In contrast, long-staying Bluethroats seem to expand their home range probably because they are in high demand of food for refueling and, perhaps, because of the competition with conspecifics and other species [START_REF] Chernetsov | Movement patterns of European reed warblers Acrocephalus scirpaceus and sedge warblers A. schoenobaenus before and during autumn migration[END_REF][START_REF] Fransson | When and where to refuel before crossing the Sahara desert extended stopover and migratory fuelling in first-year garden warblers Sylvia borin[END_REF]. If home-range size is considered a proxy of habitat quality, inland reedbeds could be interpreted as a refuge or a more optimal habitat than corn crops, which might represent the most-commonly available substitution habitat [START_REF] Godet | Differences in home-range sizes of a bird species in its original, refuge and substitution habitats: challenges to conservation in anthropogenic habitats[END_REF], where birds needing to refuel would move due to competition and the limited availability of reedbeds. In our site, Bluethroats encounter also some potentially unsuitable habitats such as woodlands, open water, mowngrasslands and infrastructures (house, road, railway) that would explain why they had to fly away a relatively long distance from their preferred roosts [START_REF] Harmange | Unexpected movements of male Bluethroats Luscinia svecica namnetum during the breeding period] Déplacements inattendus chez des mâles de Gorgebleue à miroir blanc Luscinia svecica namnetum en période de nidification[END_REF], expanding their home range size. Similar patterns have been shown in Briere for breeding Bluethroats [START_REF] Godet | Bluethroats Luscinia svecica namnetum offset landscape constraints by expanding their home range[END_REF]. We did not detect any difference between males and females in home range size, flight distance or stopover duration. Typically, small-sized, young and female Bluethroats are subordinated to large, adult and male conspecifics, respectively [START_REF] Lindström | Asymmetric contests over resources for survival and migration. A field experiment with Bluethroats[END_REF][START_REF] Moore | Priority access to food in migratory birds: age, sex and motivational asymmetries[END_REF]. Our results suggest that Barthes de la Nive was occupied, not under an ideal despotic distribution, but under an ideal free distribution, where home range size would be determined by its habitat composition.

Diet of birds and invertebrate availability

The diet description in our study site fitted well with the trophic characterization made in other Bluethroat studies (Allano et al. 1998;[START_REF] Orłowski | Partial dietary segregation between adult and nestling Bluethroats Luscinia svecica[END_REF][START_REF] Musseau | Importance of intertidal wetlands for the French coastal endemic Bluethroat (Cyanecula svecica namnetum) and conservation implications in the context of global changes[END_REF]. In decreasing order of importance, our study showed the relevance of Hymenoptera Formicidae (40.6% of prey; 8.7% of biomass), Diptera (resp. 14% and 6.5%), Coleoptera (13.7%, 40%) and Araneae (9.4%, 22.5%). Bluethroats typically forage on the ground (Orlowski et al. 2014, Allano et al. 1998[START_REF] Cramp | The Birds of the Western Palearctic[END_REF] where Formicidae are particularly abundant. As in other agricultural farms (Cornouiller et al. 1997), corn crops showed a very high insect abundance and biomass, which could explain why Bluethroats positively selected this habitat. Again and as a consequence of the relative scarcity of intertidal habitats, arthropods such as Malacostraca Amphipoda, were absent from the diet of Bluethroat in Barthes de la Nive, although they have been found in other studies [START_REF] Musseau | Importance of intertidal wetlands for the French coastal endemic Bluethroat (Cyanecula svecica namnetum) and conservation implications in the context of global changes[END_REF]Allano et al. 1998).

Habitat management implications

Our study confirmed the importance of wetlands and their associated reedbeds in Barthes de la Nive for migrating Bluethroats, as it was also shown for other bird species stopping over in the region [START_REF] Fontanilles | Sélection des habitats et occupation spatiale du Phragmite aquatique Acrocephalus paludicola sur une halte migratoire du sud-ouest de la France, mise en place d'une gestion intégrée[END_REF]. This reaffirms the need to conserve and potentially expand these valuable habitats, whose largest remnants in Southwestern France persist in the Nive/Adour river basin, and are mainly threatened by clogging and bush encroachment, particularly by invasive exotic tree species (i.e. Acer negundo, Baccharis halimifolia). So, tree expansion must be controlled in reedbeds to maintain an open wetland. Likewise, our results unexpectedly revealed a positive selection of corn crops by Bluethroats. The tall and dense arrangement of corn plants resemble the habitat structure of reedbeds. However, corn crops do not seem to constitute an ecological trap but a substitution habitat, [START_REF] Godet | Differences in home-range sizes of a bird species in its original, refuge and substitution habitats: challenges to conservation in anthropogenic habitats[END_REF] an human-induced opportunity for migrating birds. Anyway, further research would be required to further understand this this selection process and whether it also takes place in other sites. Our preliminary results suggest that corn crops would provide plenty of food resources and a suitable shelter for birds stopping over in Barthes de la Nive. Our study using the Bluethroat as model species raises the question of how other bird species respond to the presence of corn crops during their stopovers. The corn crops of Barthes de la Nive are used by a large group of migratory species (Fontanilles not published), so that measures to maintain or increase the suitability of this common crop for birds around the limited wetland remnants should be encouraged. Among them, promoting organic farming and postponing the harvesting time after mid-October, when most insectivorous migrants are in or near their southern wintering quarters, would be relatively easy to implement and might have immediate payoff [START_REF] Dänhardt | Farmland as stopover habitat for migrating birds effects of organic farming and landscape structure[END_REF].

ACKNOWLEDGEMENTS -This work was supported by the Conseil Départemental des

All data and information from external sources used for the analyses and preparation of the manuscript are properly cited. The conclusions are entirely based on our own results. All applicable