Complex Day-to-day Movements of an Alpine Passerine May Act as an Insurance Against Environmental Variability

Mountains naturally offer very contrasting habitat conditions, but their biodiversity is nowadays facing the extra challenge of adapting to rapid environmental shifts that are much more pronounced than in the lowlands. Among the possible adaptive responses of wildlife, intra- and inter-seasonal movements represent an important coping strategy that remains largely unexplored. We investigated the seasonal and day-to-day movements of the ring ouzel Turdus torquatus, a European mountain bird species that is declining in many parts of its distribution. We tracked individuals breeding in the Swiss Alps using geolocators, multi-sensor loggers and GPS. Of the birds traced to their non-breeding quarters, two thirds reached the Atlas Mountains while one third stayed in Spain, a region potentially more signicant for overwintering than previously thought. The birds remained mostly above 1000 m throughout the annual cycle, highlighting a strict association of ring ouzels with mountain habitats. We also evidenced exible daily elevational movements, especially upon spring arrival on the breeding grounds, which suggest adaptive potential in response to environmental variation. This study shows how modern technology can deliver deeper insights into animal movements, paving the way for rened assessments of species vulnerability to ongoing global change while providing basic conservation guidance.


Introduction
Information on year-round movement patterns is key for animal species conservation (Webster et al. 2002). In effect, migratory decisions can directly determine individual survival and reproductive success (Gill et al. 2001;Marra et al. 1998), impacting population dynamics (Norris and Marra 2007). The majority of animals inhabiting highly seasonal environments such as arctic and alpine ecosystems occupy their breeding habitat only during the short warm season. Consequently, the timing arrival at, and departure from these grounds needs to be nely tuned to the brief time window available for reproduction (Wing eld et al. 2004;Winkler et al. 2014). Given the particularly rapid pace of the environmental changes affecting these ecosystems (Flato and Boer 2001;Pepin et al. 2015), the capacity of birds to adjust and time their movement decisions in response to environmental shifts will be crucial for their long-term persistence (Dolman and Sutherland 1995;Winkler et al. 2014).
Movements of wildlife in mountain ecosystems have been little studied, even among well-investigated taxa such as mammals and birds of temperate biomes (Boyle and Martin 2015;Resano-Mayor et al. 2017). For instance, within-breeding season movements (Ceresa et al. 2020;Frey et al. 2016) or facultative latitudinal migration of bird species long considered as resident  have been unveiled only recently, adding to our historical knowledge of seasonal elevational migration (Barçante et al. 2017;Hsiung et al. 2018;Tsai et al. 2021). In the same line, the importance of highelevation ecosystems as post-breeding or stopover grounds for migratory species may have been widely underestimated (Boyle and Martin 2015). The pronounced spatiotemporal heterogeneity that characterizes mountain ecosystems thus appears to foster regular movements throughout the annual cycle (Martin 2001), both latitudinally and elevationally. However, individual dispersal has remained poorly documented until the recent deployment of sophisticated tracking technology.
The rapid development of tracking devices offers novel opportunities to study individual bird movements at unprecedented spatial and temporal scales and thus to tackle key conservation challenges (Katzner and Arlettaz 2020). For small birds, geolocators (GL) enable tracking individuals throughout the annual cycle by means of simple measures of light intensity coupled with an internal clock. Still, this technology alone is not accurate enough to detect small-scale latitudinal movements (Fudickar et al. 2012), without mentioning elevational ones. This is possible with GPS tracking devices, which are now successfully deployed on small passerines (McKinnon and Love 2018), but the reduced lifespan of the embedded battery drastically limits the number of locations that can be collected. More recently, multi-sensor loggers (MSL) that combine GL with other sensors such as barometers and accelerometers have been developed . Similarly to GL, MSL can collect data at high frequency and over long periods of time, additionally providing much deeper insights into individual spatial behaviour, including activity patterns, migratory schedules and ight altitude (Briedis et al. 2020;Dhanjal-Adams et al. 2018;Liechti et al. 2018). They thus represent a promising tool to better assess the three-dimensional movements of small animals such as passerines.
We investigated the annual movement patterns of a Western Palearctic passerine, the Alpine ring ouzel (Turdus torquatus alpestris), using these new tracking technologies. This subspecies of thrush breeds primarily in the mountain massifs of western and central Europe, from the Cantabrian to the Carpathian Mountains (Glutz von Blotzheim and Bauer 1988;Keller et al. 2020). It is believed to overwinter mainly in the Atlas Mountains in Morocco and Algeria (Glutz von Blotzheim and Bauer 1988) -in sympatry with individuals from the northern subspecies T. t. torquatus (Bur eld 2002;Sim et al. 2015) -where the principal source of food is juniper (Juniperus sp.) berries (Ryall and Briggs 2006). Nonetheless, winter observations at the southern boundary of species breeding range (French western Alps and Pyrenees; Glutz von Blotzheim and Bauer 1988) suggest that central European populations are partially migratory or travel much shorter distances than their northern conspeci cs, a classical pattern among European migrants (i.e. leapfrog migration; Newton 2008). Given the population declines observed in various parts of the species range, in particular at its periphery, it has been suggested that hunting and habitat deterioration in the principal migratory stopovers and/or on winter quarters may add to drivers negatively impacting the species on its breeding grounds (Bur eld 2002; Sim et al. 2015). Yet, large-scale movements and thus migratory connectivity of the different ring ouzel populations are still poorly documented (Sim et al. 2015). Here, we used various tracking technologies to unravel the migration timing, routes and behaviour of ring ouzels breeding in the Central European Alps.

Fieldwork and material
Birds were captured and ringed at a single study site in Valais, Switzerland (46.33 N,7.43 E; 1800-2100 m above sea level) during the breeding season, i.e. in April-June 2015-2020. Captures were performed with 2.5-m high mistnets placed among potential foraging grounds or parallel to forest edges. Birds were sexed from plumage coloration and age -either second calendar year (2cy) or adult (>2cy) -determined based on the presence of a moult limit in the greater coverts (Jenni and Winkler 2020).
We used four types of loggers to record ring ouzel locations: simple geolocators (hereafter GL; model GDL2, Swiss Ornithological Institute (SOI), Switzerland); remote-download geolocators (hereafter also termed GL; model GDL-uTag, SOI, Switzerland); multi-sensor loggers (hereafter MSL; model GDL3-PAM, SOI, Switzerland) and GPS loggers (GPS; model nanoFix-GEO, PathTrack Ltd, UK). In addition to light intensity, the deployed MSL measured acceleration and atmospheric pressure at 5-min intervals (see Liechti et al. 2018 for details). GPS were programmed to record position once a week. All types of loggers were xed on the birds using a leg-loop harness, made of elastic rubber or inelastic threaded nylon as concerns GL and MSL, and Te on ribbon for GPS. The different types of loggers (see details in the Supplementary Table S1) weighed at most 2.6% of the mean (± SD) body mass as measured from captured birds (males: 95.1 ± 5.1 g, n = 191; females: 100.8 ± 8.9, n = 91). The permit for bird capturing was delivered by the Swiss Federal O ce for the Environment (F044-0799) and tting of tracking devices was authorized by the Swiss Federal Food Safety and Veterinary O ce, with all study protocols approved by the responsible ethics committee. Capturing and tagging were performed following all relevant guidelines and regulations of the abovementioned federal o ces.
We equipped a total of 59 individuals with 62 GL or MSL (three individuals were equipped twice) as well as 15 individuals with GPS between 2015-2019 (see Supplementary Table S1). Only seven out of the 62 GL/MSL were retrieved by recapture of the tagged bird, while data from another four GL could be downloaded remotely in the eld. Two additional GL-tagged individuals had lost their logger at the time of recapture. We thus retrieved data from, in total, 5 MSL and 6 GL. For MSL, data was complete (over one year) except for one device that had stopped recording as early as February in the year following tagging. Regarding GL, intense shading prevented data exploitation for two of them. Shading by feathers or the surrounding habitat may indeed strongly bias the measurements of sunrise or sunset times (hereafter twilights) and lead to spurious localizations. We additionally retrieved two out of the 15 GPS by recapture but both had malfunctioned, with locations available for only one GPS for just a month after deployment.
On subsequent years following ringing, we re-sighted 33.9% (20/59) of the individuals equipped with GL and MSL, and 20% (3/15) of the GPS-tagged birds, to be compared with 29.9% (64/214) of the ring ouzels that had only been colour-ring marked at the study site and served as a control group. As assessed with Bayesian Cormack-Jolly-Seber models from visual re-sightings (following Kéry and Schaub 2012), apparent survival rates of GL-and MSL-tagged birds did not differ from the control group (β = 0.27, 95% CI: -0.92 to 1.66), while we evidenced a detrimental effect of the slightly heavier GPS loggers (β = -1.74, 95% CI: -3.32 to -0.42).

Analyses
All analyses were performed with the software R version 3.6.2 (R Development Core Team 2019) using the packages TwGeos (Wotherspoon et al. 2016), GeoLight (Lisovski and Hahn 2012), SGAT (Sumner et al. 2009) and PAMLr (Dhanjal-Adams 2019), following the general framework described in Lisovski et al. (2020). Starting with data from the ve MSL, we classi ed bird behaviour into four categories of activity (no activity, low activity, high activity and migration) based on acceleration measures, using the algorithm from the classifyFLAP function in PAMLr. We de ned migratory ights as those equal or longer than 30 min, which corresponds to at least six consecutive readings with ascertained ight activity. Based on this data, we de ned the migratory schedule and separated the annual cycle into four periods: post-breeding, autumn migration, non-breeding (i.e. overwintering) and spring migration (the locations during reproduction being irrelevant here). The post-breeding period started on the day of the rst nocturnal ight in June or July and lasted up to the autumn migration departure, which was de ned as the rst true migratory ight after August 1 st . We assumed that birds had reached their non-breeding residence area as soon as they had stayed for at least two weeks in a row at the same place after October 1 st . Spring migration started with the rst ascertained migratory ight in March.
In a second step, we converted readings of atmospheric pressure into m above sea level (hereafter m asl) using the function altitudeCALC in the PAMLr package, which is based on the hypsometric equation that assumes standard atmospheric conditions Stull 2016). Hence, estimates of elevation are rather precise, but can be biased by natural variations in atmospheric pressure, i.e. in uenced by the so-called «high-and low-pressure areas». Such shifts in pressure are, however, fairly slow and minor (maximum of 2 hPa h -1 ) so that they would not generate abrupt changes in estimated elevation . Furthermore, daily uctuations in atmospheric pressure, called atmospheric tides, reach at most winter. To t the Estelle model, we rst drew 1'000 initial samples using a 'modi edGamma' model (i.e. relaxed model, allowing negative errors on twilight times), tuned it 5 times with 300 iterations using a 'Gamma' distribution. We shall here report median estimates ± 95% credible intervals (CI; based on 2.5 and 97.5% quantiles) from a nal run with 2'000 iterations to ensure convergence.

Migratory schedule
We obtained a complete annual migratory schedule for four individuals, and partial for a fth (Table 1).
Most of the migratory movements (i.e. ights ≥ 30 min) took place at night (mean = 96.7%, range: 92.7-98.8%). Post-breeding dispersal started between the second half of June and the rst 10 days of July (Table 1), although it consisted of only one single short nocturnal ight (< 30min) for bird AdM-3 (Fig. 1).
Actual departures into fall migration were observed 45-103 days after the onset of post-breeding dispersal, differing markedly between all ve individuals ( Table 1). Most of the autumn migratory ights occurred in October for all birds ( Fig. 1; Supplementary Fig. S1). Inter-individual differences in the onset of fall migration resulted in a large variation in the duration and speed of migration (Table 1), but the cumulative sum of ight hours varied little in all three adult males, with 44, 43 and 45 h, respectively (AdM-1, -2, -3; Table 1, Supplementary Fig. S1). The ight duration of the sole adult female (AdF) with a full tracking record was much briefer (31 h), owing to the shorter distance to her non-breeding site (Table   1). A fourth younger male (second calendar year; 2cyM) revealed high migratory activity in August and September already, resulting in a total of 75 h in migratory ights. The number of days necessary to reach the nal non-breeding destination varied between 27 and 55 days (except for 2cyM that was hyperactive in the late summer, see above), although migratory ights occurred only during 7-13 nights (31 nights for 2cyM). Nocturnal migratory ights were also obvious for two individuals (2cyM and AdM-1) in December and January (Fig. 1), evidencing potentially signi cant movements in the middle of the winter ( Supplementary Fig. S2). Spring migration from the four birds that yielded data took place in a fairly narrow temporal window of 9-20 days ( Table 1, Fig. 1), being thus much shorter than fall migration, and also briefer in cumulative ight hours and number of migratory nights (Table 1).

Migration routes
An insu cient quality of data combined with migratory activity typically taking place around the equinoxes dramatically limited our ability to precisely reconstruct the migratory trajectories and locate the stopovers for most of our birds. Nevertheless, the GPS information available from a single bird revealed a 140-km eastwards movement at the end of June and early July (over 20 days), hence initiating postbreeding dispersal, in line with the ndings obtained with MSL. However, nocturnal ight durations of MSL-tagged birds at that time of the year (0.25-4.7 h in total) suggest that only one other bird could have covered a similarly long distance during the post-breeding period (AdM-2; Fig. 1). Concerning nonbreeding grounds, GL and MSL data revealed that six birds spent the winter in North Africa, while three others most likely overwintered in the Iberian Peninsula (Fig. 2). Among the six birds wintering in Maghreb, two were localized in the Middle Atlas, two in the High Atlas and one in the Anti-Atlas, all ve in Morocco. The location estimates of a sixth bird (2cyM) further south in Algeria are inconsistent with elevation readings (Fig. 3) and probably biased southwards (see also Supplementary Fig. S2); this individual may actually have overwintered in the Anti-Atlas or High Atlas massif. Among the three ring ouzels staying in Spain, one individual overwintered in the meridional Sistema Ibérico, (AdM-4), another in the Sistema Prebético (AdF), while the winter quarters of the third bird (AdM-5) are unclear (average locations in the Mediterranean) and could be situated in the eastern part of the Sistema Prebético (Fig. 2).

Elevational movements
The median elevation during the post-breeding period was, for all ve birds tagged with MSL, above the average elevation of the core study area (i.e. >1950 m asl; Fig. 3), indicating movements to sites mostly above the timberline after reproduction. The median elevation of stopovers during the autumn migration (in contrast to their location, the elevation of stopovers was easily retrieved from barometer data) was generally above 1860 m asl (Fig. 3), but three birds stopped below 1000 m asl for a single day. The maximal estimated ight elevation was reached during the fall nocturnal migration by bird AdF on October 10 th , with 4270 m asl. The median elevation of non-breeding grounds was always greater than 1500 m asl for every individual, irrespective of their location. Spring stopover sites were on average at a lower elevation than autumn stopovers (Fig. 3). Finally, year-round measurements revealed periods with marked elevation differences between day and night within a 24-h cycle ( Supplementary Fig. S3). Birds were then clearly commuting every day to areas located either below (pre-breeding) or above (postbreeding) the elevation of their location overnight. This phenomenon, con rmed via direct eld observations, was particularly marked during the two to three weeks following spring arrivals, when birds ew to foraging grounds situated several hundred meters below the breeding area (Fig. 4). A similar behaviour was also detected later in the season, following late snowfalls (Fig. 4).

Discussion
Using electronic tracking technology, we documented the seasonal movements of Alpine ring ouzels breeding in the Swiss Alps. From a technical viewpoint, if modern tracking methods offer new opportunities for in-depth ecological research, we must not forget that geolocation is particularly challenging when deployed in mountainous environments. This is because the complex topography in uences the measurement of day length, yielding less accurate location estimates. Multi-sensor loggers may constitute a valuable alternative as they enable measuring elevation and behaviour at an unprecedented ne temporal resolution. Here, it is the combination of different methods that provided us with a clear picture of the year-round locations and migratory behaviour of the ring ouzel. We found that the species is tightly associated with mountain ranges and high elevations at all stages of its life cycle, including during migratory stopovers. This highlights that temperate mountain ecosystems are important not only for the reproduction of Western Palearctic avifauna but also for its dispersal and migration, in line with what has been documented in the Nearctic (Boyle and Martin 2015;Martin 2001). For the ring ouzel, mountain massifs actually constitute a network of stepping stones in the western European landscape that is otherwise dominated by unsuitable lowland habitat. The behavioural pattern illustrated here may be partly shared by at a least another typical inhabitant of European alpine ecosystems, the white-winged snow nch Montifringilla nivalis (see Resano-Mayor et al. 2020). Given the faster climate shifts at high elevations (Pepin et al. 2015) and shrinking habitat due to the pyramid shape of mountains, these mountain species are regarded as especially vulnerable to rapid climate change (La Sorte and Jetz 2010). The strict reliance on mountains for various parts of the annual cycle might render them even more sensitive, compared to other alpine species which also use lowland habitats (e.g. northern wheatear Oenanthe oenanthe or water pipit Anthus spinoletta).
Our results con rm the important role played by the Atlas Mountains for wintering ring ouzels (Glutz von Blotzheim and Bauer 1988;Ryall and Briggs 2006;Sim et al. 2015): two thirds of our birds spent the cold season in Maghreb. The remaining third overwintered in the Iberian Peninsula, suggesting that Spanish mountain ranges may represent another, so far unrecognized key wintering hotspot, at least for the Alpine population. Observations of ring ouzels in winter in the Atlas and Spanish massifs have shown that they feed mainly on juniper berries (of Juniperus thurifera, communis, oxycedrus, phoenica and cedrus), playing a key role in seed dispersal (Herrera 1985;Rumeu et al. 2009;Ryall and Briggs 2006;Zamora 1990). Overwintering in Spain certainly entails shorter, i.e. energetically less demanding ights for Alpine ring ouzels. Nonetheless, the reason for choosing Spain may lie elsewhere. In effect, the fructi cation of junipers is highly cyclic in the Spanish highlands (Tellería et al. 2014;Tellería et al. 2011), as it probably also is in North Africa (Ryall and Briggs 2006). Since thrushes are known to actively track food sources (Tellería et al. 2014;Tellería et al. 2011), the local availability of juniper berries probably explains the whereabouts of ring ouzels in winter. Hence, the few sudden movements we could document in winter may correspond to relocations to regions providing good food supplies. An ability to move between feeding areas could make ring ouzels somehow resilient to the progressive loss of their foraging habitat in the Maghreb, notably in Morocco where juniper forests are systematically overexploited for rewood (Ryall and Briggs 2006).
Finally, we also evidenced complex patterns of elevational movements. First, birds retreated to lower elevations following late snowfalls in spring. These movements triggered by adverse weather conditions at the breeding site have been described for numerous bird species in several mountain ranges (Boyle et al. 2010;Hahn et al. 2004;O'Neill and Parker 1978). More surprisingly, ring ouzels also performed daily elevational movements that have to our knowledge never been documented in such detail at the individual level apart from aerial insectivores (see Dreelin et al. 2018). The most patent demonstration of this phenomenon was upon arrival of ring ouzels on their Alpine breeding grounds in April, when those are still covered by a dense snowpack. Birds typically overnight in their future breeding territories, males vocally signaling their occupancy at dawn and dusk (Glutz von Blotzheim and Bauer 1988). The rest of the day, they apparently visited snow-free meadows at lower elevations to forage, usually in the montane and subalpine belts, depending on seasonal, year-speci c snow conditions (Fig. 4). Later in the season, with the advancement of the snowmelt which frees the rst patches of alpine grasslands within the breeding area, they stopped commuting. Daily elevational migration may enable birds to settle in highelevation breeding grounds very early in the year, sometimes when those are still inhospitable, and thus some sort of insurance against missing the brief time window suitable for breeding (Barras et al. 2020;Barras et al. 2021). Indeed, ring ouzels migrate much faster in the spring than in the autumn, a pattern commonly observed across various migration yways and species (Nilsson et al. 2013;Schmaljohann 2018). However, this contrasts with the migration strategy of other mountain or arctic bird species, that make prolonged pre-breeding stopovers at lower elevations or latitudes not far from their reproductive grounds, waiting there for the snowmelt at their nearby breeding sites and/or building fat reserves (de Zwaan et al. 2019;Kölzsch et al. 2016). With their daily elevational movements, ring ouzels have thus found an innovative solution to cope with the highly seasonal and unpredictable breeding environment that prevails at high elevation. The question remains whether this high spatial exibility will also procure ring ouzel -and other cold-adapted bird species (Hahn et al. 2004;Resano-Mayor et al. 2020;Wing eld et al. 2004) -some buffer against the dramatic impacts of climate and land-use change that are going to accentuate into the future.

Declarations
Acknowledgements: We are indebted to all people who helped with eldwork, in particular J. Resano-Mayor, I. Candol and Y. Rime. We are also grateful to E. Baechler and N. Znakovaité for technical support, as well as K. Dhanjal-Adams for the assistance in data processing. We thank MeteoSwiss for providing weather data.
Funding: FL was supported by the Swiss Federal O ce for the Environment for geolocator development 332,363,400).
Author contributions: All authors contributed to the study conception and design. Data collection and analysis was performed by AB. AB lead writing of the manuscript and all authors read, thoroughly edited and approved the nal manuscript.
Con icts of interest: The authors declare that they have no con ict of interest Permit: Permission for bird capturing was delivered by the Swiss Federal O ce for the Environment (F044-0799) and authorization for tting birds with tracking devices by the Swiss Federal Food Safety and Veterinary O ce.
Data accessibility statement: Data that support the ndings of this study will be made available from the gshare repository upon publication.  Actograms of ve ring ouzels equipped with multi-sensor loggers, showing the annual activity pattern as classi ed into four categories of behaviour. Small white squares show the timing of the twilights as estimated from the individual light sensor of the tag. The cut between two successive 24-h periods is set at noon to enhance the visualization of a nocturnal migratory ight along a single line.

Figure 2
Longest stationary winter locations of nine ring ouzel individuals as retrieved from geolocator data. Error bars around locations represent 95% credible intervals while the size of circle is proportional to stay duration. Winter sightings of ring ouzels (December to February) are shown as small black dots and were accessed via GBIF (https://doi.org/10.15468/dl.p6ez7a). Areas shaded in dark grey are above the contour line of 1000 m asl.

Figure 3
Median elevation estimates, at four stages of the annual cycle, for ve ring ouzels equipped with multisensor loggers. For autumn and spring migration, readings during stopovers (circles) are separated from those during active, mostly nocturnal migration (triangles). Bold bars represent the lower to upper quartile range and thin bars the total range of readings (min to max).

Figure 4
Continuous elevation estimates (5-min intervals) from four ring ouzels upon arrival (date: vertical dotted line) on the breeding grounds in spring. Grey zones symbolize nighttime and the horizontal dashed lines indicate the mean elevation of the study area. Elevation estimates displayed in red refer to migratory ights. Snow ake icons indicate a new snowfall (≥ 1 cm fresh snow) as measured at a nearby weather station (4.1 km distance, 2390 m asl).