In recent years, advances in tracking technology have greatly improved our understanding of bird migration (Wikelski et al., 2007; Kays et al., 2015; Jetz et al., 2022; Kays and Wikelski, 2023). By tracking tagged birds, we can study various migratory behaviors, such as their propensity to migrate, connectivity and philopatry, length of migration routes, variations in flight speed, and movements within a single season (Alerstam et al., 2003; Newton, 2008; Alerstam, 2011; Berthold et al., 2013; Trierweiler et al., 2013; Schlaich et al., 2023). Different combinations of these behaviors contribute to various bird migration patterns (Chapman et al., 2014; Alerstam and Bäckman, 2018; Lislevand et al., 2020). Understanding the migratory patterns of birds is critical to accurately map their ranges and estimate their population trends. Typically, population trends are assessed in breeding areas, where birds are linked to their nesting sites, allowing reliable estimates of breeding numbers (Reif, 2013). However, access to some breeding areas, such as the Arctic, presents logistical and political challenges (Gallo-Cajiao et al., 2023; Koivurova and Shibata, 2023). As a result, population trends for these species are often estimated in over-wintering ranges where birds are not tied to specific locations (Robinson et al., 2005; Jia et al., 2016). This challenges accurately censusing birds and delineating their ranges, especially when birds move extensively in over-wintering ranges during the season, and censuses are conducted only once per over-wintering season. Therefore, understanding bird movements in over-wintering ranges is essential for understanding the ecology of birds in these regions and has practical implications for accurately assessing their ranges and trends in their populations.

Many bird species experience significant seasonal changes in food availability within their over-wintering range due to environmental conditions. This often triggers movements across these areas. For Palearctic migrants wintering in Africa, these movements have been studied extensively (Moreau, 1972; Trierweiler et al., 2013; Thorup et al., 2017; Schlaich et al., 2023). However, the over-wintering movements of mid-latitude birds remain poorly understood. At the same time, many Arctic birds overwinter in the mid-latitudes, and understanding their movement patterns could be crucial for interpreting their population trends. In the mid-latitudes, food availability is strongly influenced by environmental factors such as snow cover dynamics. The progressive movement of the snow cover line from north (-east) to south (-west) and back again between October and May in many mid-latitude regions, particularly those exposed to northwesterly wind systems, significantly affects food availability for numerous bird species (Sonerud, 1986; Vansteelant et al., 2011). We propose that species dependent on this environmental factor gradually move away from snow-covered areas during winter and then gradually move back in the opposite direction, resulting in a directed and continuous displacement of their over-wintering range.

The Rough-legged buzzard (Buteo lagopus) is an Arctic breeding and mid-latitude wintering raptor (Ferguson-Lees and Christie, 2001; Bechard and Swem, 2002). Rough-legged buzzards feed mainly on small rodents in the Arctic and its wintering grounds (Tast et al., 2010; Pokrovsky et al., 2014). They prefer open areas for hunting, and trees and tall bushes or uplands for resting and nesting. In the Arctic, where they nest, these habitats are in the southern and typical tundra zone (Walker et al., 2005). In the mid-latitudes, where they overwinter, these habitats are in the zone of fields with scattered patches of forests (wooded fields). The taiga zone, located between the tundra and wooded fields zones, offers limited open space, and is generally unsuitable for the species, although they may nest in the northern taiga near the tundra zone (Sundell et al., 2004). Thus, Rough-legged buzzards migrate from the Arctic through the taiga zone to the wooded fields zone for wintering. However, environmental conditions in the mid-latitudes vary, potentially influencing their migratory behavior.

The spatio-temporal latitudinal and longitudinal gradients in environmental conditions impact bird populations (Kiat et al., 2021). Deep snow covers the northeastern regions of suitable wintering habitats (wooded fields) during mid-winter, significantly hindering the Rough-legged buzzards' ability to hunt small rodents (Sonerud, 1986; Vansteelant et al., 2011; Terraube et al., 2015; Curk et al., 2020). Simultaneously, many Arctic migrants prefer winter as close to the Arctic as possible to shorten their return to breeding grounds and extend the breeding season (Berthold et al., 2013). Therefore, we can anticipate three potential non-exclusive migration strategies for Rough-legged buzzards: (1) birds may migrate through the taiga and northeastern wooded fields zones to the southwestern areas with less snow cover during winter, (2) birds may stop in the wooded fields zone after crossing the taiga and move southwest in mid-winter when snow cover makes hunting rodents impossible, eventually migrating back to the breeding grounds from southwestern regions, (3) alternatively, similar to the second strategy, birds may move southwest but return to the northeastern wooded fields zone after mid-winter to be closer to the breeding grounds, and migrating to the Arctic from there.

In this study, we tracked GPS-tagged Rough-legged buzzards for 10 years and analyzed their movements in the over-wintering mid-latitude range in relation to snow cover. For this study, we made the following predictions. (1) Rough-legged buzzards could exhibit a directional and seasonal movement pattern during the over-wintering period, moving from the northeast to the southwest and back again. This would result in a dynamic over-wintering range that would continue to move geographically throughout the season. (2) The over-wintering movements would differ from the fall and spring migrations in duration, extent, speed, and direction but would continue throughout the season. Thus, over the entire annual cycle, Rough-legged buzzards would be characterized by a migratory pattern consisting of an alternation of quick (fall and spring migrations) and slow (over-wintering movements) phases. (3) Over-wintering movements would occur in suitable open habitats, while fall and spring migrations would occur in unsuitable forested areas. Thus, vegetation land cover will determine the extent of quick and slow migration phases. (4) During over-wintering movements, Rough-legged buzzards will experience less snow cover than if they had stayed where they arrived at the end of the fall migration. Thus, snow cover dynamics will determine the dynamics of over-wintering movements.

Our study identified and characterized a bird migration pattern consisting of an alternation of quick (fall and spring migrations) and slow (over-wintering movements) phases. This migration pattern causes the over-wintering range of birds to shift and become dynamic throughout the season. This has obvious implications for range delineation and assessment of bird population trends.

Over-wintering movements and migratory patterns

Different bird species employ various wintering strategies, leading to diverse migration patterns. One strategy is ‘residency’, where birds arriving at over-wintering grounds remain there throughout the season, undertaking only minor foraging flights (Figure 4a). Their home ranges in over-wintering ranges are compatible with those in breeding ranges (Kjellen et al., 1997; Alerstam et al., 2006; Newton, 2008). Another strategy, initially identified by Moreau, 1972, is ‘itinerancy’, wherein birds fly between several sites separated by distances ranging from ten to several hundred kilometers throughout the over-wintering period, spending 1–2 months at each site (Figure 4b). Most Palearctic-African species adopt this itinerant behavior (Trierweiler et al., 2013; Thorup et al., 2017; Schlaich et al., 2023). The third strategy investigated here involves birds moving slowly and steadily throughout the over-wintering season, initially in one direction and then in the opposite direction. In 2009, Roine Strandberg and his colleagues used GPS transmitters to track Common buzzards (Buteo buteo). Despite some transmitters in their study ceasing to function mid-winter, the authors observed a phenomenon they termed ‘prolonged autumn migration’, wherein birds arriving at their wintering grounds did not halt migration but continued moving at a slower pace (Strandberg et al., 2009). In our study, we observed this phenomenon throughout the annual cycle. We demonstrated that, unlike itinerancy, movements in the over-wintering range are essentially a continuation of migration at a slower pace, influenced by external factors such as snow cover dynamics. Considering this behavior as an extension of migration and examining the complete life cycle of such species, it involves a quick phase during the transition between breeding and over-wintering ranges, followed by a slow phase of directed and seasonal movement within the over-wintering range, and finally, another quick phase toward the breeding range. Drawing an analogy to the alternating quick and slow movements of the foxtrot dance, we propose the term ‘foxtrot migration’ for this seasonal movement to offer a concise and easily understandable description (Figure 4c). Consequently, we suggest referring to the over-wintering range of species exhibiting itinerancy or foxtrot migration as the ‘dynamic range’ (Figure 4b and c).

Figure 4

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Debates may arise regarding introducing a new term for this phenomenon and whether it should fall under the general term ‘nomadism’ or be categorized as a modified form of another migratory pattern, such as ‘slow directional itinerancy’. We assert that behavioral pattern names should aid in understanding movement strategies and avoid confusion. One might ask whether it is necessary to distinguish between migration and wintering at all, given that migration is essentially a matter of tracking spatial and temporal changes in favorable conditions. Authors studying Montagu’s harriers (Circus pygargus) argue that such generalization hampers understanding of wintering strategies (Schlaich et al., 2023). Instead, Schlaich et al., 2023 propose explicitly considering the functions of animal-used sites, particularly their contributions to ‘wintering’ and ‘refueling for migration’. For instance, cuckoos (Canorus sp.) utilize stopovers for both peak foraging conditions and refueling for long flights to subsequent sites (Thorup et al., 2017). Conversely, Montagu’s harriers exhibit negligible refueling between sites due to short distances and energy-efficient soaring flight (Trierweiler et al., 2013; Schlaich et al., 2023). In our case, Rough-legged buzzards do not make several long stopovers, unlike species experiencing itinerancy, but move gradually in one direction and then return during the whole season (Figure 1a). As Schlaich et al., 2023 suggested, examining the functions of animal-used sites reveals another difference between these strategies. The difference is that itinerant birds wait for better conditions at subsequent sites. In contrast, in our case, the southwestern areas that birds reach after several months are suitable and offer better conditions than the northeastern areas as they have less snow throughout the whole over-wintering season (Figure 3). All these differences highlight the discrepancy between the wintering strategies referred to as itinerancy and those described in this study. Therefore, using another term – foxtrot migration – for this phenomenon is more appropriate.

Mapping ranges and assessing population trends

The implementation of our study is twofold: (1) the use of mid-winter bird surveys to determine over-wintering range may yield inaccurate results for species with dynamic range (Figure 5a), and (2) declines in abundance within a particular segment of the over-wintering range may indicate changes in range dynamics rather than widespread declines in species abundance (Figure 5b).

Figure 5

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In North America and Europe, the number of over-wintering birds is typically estimated once a season in mid-winter. In North America, these estimates are made during the Christmas counts, usually once in late December (National Audubon Society, 2024), while in Europe, they are made during the IWC counts, usually once in January or February (Wetlands International, 2024). This approach can lead to errors in range estimation for birds with dynamic ranges. For such species, habitats occupied by birds in fall and spring will be listed as ‘uncommon’ at best, while habitats occupied by birds only in mid-winter will be listed as ‘common’. However, the situation is the opposite if we consider the time birds spend in these habitats (Figure 5a). For example, based on our study of the Rough-legged buzzard, during mid-winter, the species is predominantly present in the southwestern portion of its over-wintering range, with only a tiny proportion present in the rest of the region. As a result, a map of the over-wintering range may show the species as ‘common’ in the southwest and ‘uncommon’ in the northeast. This map would be inaccurate because, during the entire over-wintering period, Rough-legged buzzards spend both fall and spring in the northeastern part and only mid-winter in the southwestern part.

To address this, continuous year-round GPS tracking of the species provides a means to track bird locations throughout the over-wintering season, facilitating the creation of accurate distribution maps, particularly for species that exhibit dynamic ranges. We advocate representing temporal heterogeneity (range dynamics) on maps as distinct zones, denoting periods when the species is abundant in a given area. To distinguish temporal from spatial heterogeneity, we recommend using lines to delineate the boundaries of these zones, rather than color shading, and incorporating numbers to denote the months of species abundance in a given zone (Figure 5a). We suggest ecologists include dynamic over-wintering ranges in descriptions and range maps for foxtrot migratory and itinerant bird species.

Population counts for a species are often limited to a portion of its range. Therefore, conclusions about conservation status drawn from such counts may be misleading. A decline in abundance within a particular portion of the over-wintering range may indicate changes in range dynamics rather than a general decline in the species (Figure 5b). For example, climate change may affect snow cover dynamics, reducing its intensity in northern regions. As a result, species whose range dynamics depend on snow cover may choose to remain in the northern areas and not migrate as far south as they traditionally have. Despite this shift in range dynamics, overall species abundance may remain unchanged. Similar patterns have affected Rough-legged buzzards in some areas of the European over-wintering range.

A 2022 Dutch study found a decline in wintering Rough-legged buzzards over the last 40 years (Hornman and Boele, 2022). On the one hand, this may represent a conservation concern. On the other hand, applying the rationale of the dynamic range, the apparent local decline may be attributed to climate change, resulting in less comprehensive snow coverage in the northeastern wintering areas of Rough-legged buzzards relative to the Netherlands. Such a shift in snow coverage makes it less probable for the birds to migrate to the Netherlands for over-wintering. This proposition is further supported by a study of the winter population dynamics of Rough-legged buzzards in the Netherlands in 2011, showing that the main winter population peak occurred in late December, with many birds migrating (Vansteelant et al., 2011). Vansteelant et al., 2011 also found that the main migration occurred after heavy snowfall in northern Europe, supporting our foxtrot migration explanation for this decline. Therefore, investigating the dynamic range is critical to understanding a species' range and effectively assessing its conservation status.

Tracking data have been deposited in the Movebank Data Repository.

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Author details

1. Ivan Pokrovsky

   Department of Migration, Max Planck Institute of Animal Behavior, Radolfzell, Germany

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   ipokrovsky@ab.mpg.de

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6533-674X

2. Teja Curk

   Leibniz Institute for Zoo and Wildlife Research, Berlin, Germany

   Contribution

   Formal analysis, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

3. Andreas Dietz

   Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Wessling, Germany

   Contribution

   Formal analysis, Funding acquisition, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

4. Ivan Fufachev

   Institute of Plant and Animal Ecology, Yekaterinburg, Russian Federation

   Contribution

   Formal analysis, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

5. Olga Kulikova

   Institute of the Biological Problems of the North, Magadan, Russian Federation

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

6. Sebastian Rößler

   Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Wessling, Germany

   Contribution

   Resources, Data curation, Formal analysis, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

7. Martin Wikelski

   1. Department of Migration, Max Planck Institute of Animal Behavior, Radolfzell, Germany
   2. Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany

   Contribution

   Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Project administration, Writing - review and editing

   Competing interests

   No competing interests declared

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