Flight altitude of common cranes (Grus grus) crossing the Arkona Basin (Baltic Sea): implications for offshore wind farm development

Flight altitude of common cranes (Grus grus) crossing the Arkona Basin (Baltic Sea): implications for offshore wind farm development | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Ecology and Evolution This is a preprint and has not been peer reviewed. Data may be preliminary. 3 September 2025 V1 Latest version Share on Flight altitude of common cranes (Grus grus) crossing the Arkona Basin (Baltic Sea): implications for offshore wind farm development Authors : Henrik Skov 0000-0001-8835-3166 [email protected] , Stefan Heinänen , Lars O. Mortensen 0000-0002-8879-1382 , Johan Månsson 0000-0002-5189-2091 , Lovisa Nilsson 0000-0003-4822-7864 , Rune Tjørnløv , and Ramūnas Žydelis Authors Info & Affiliations https://doi.org/10.22541/au.175692142.22513960/v1 Published Ecology and Evolution Version of record Peer review timeline 322 views 167 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The common crane (Grus grus), like other soaring species of birds, uses a migration strategy to minimise the risk of wind drift over open sea, resulting in aggregation of birds along migratory corridors. With the planned large-scale development of offshore wind farms there is a need for an improved understanding of the potential interactions between cranes and the wind turbines as they cross the sea during migration. By using laser rangefinder tracking and GPS-tagged crane individuals we studied the vertical flight behaviour in relation to weather conditions as they cross the Arkona Basin between Sweden and Germany. The effect of weather conditions on the vertical distribution (i.e. flight altitudes) of the cranes was modelled using generalized additive mixed models. The results show that the flight altitude of common cranes crossing the basin strongly depends on the wind and visibility conditions. Both during the spring and autumn migration the cranes utilise thermal winds at the coast to soar, and frequently reach altitudes >300 m. Despite variability in wind and visibility conditions, the model predictions showed that the flight altitude descended towards the central offshore parts of the basin with a steeper descending trend during headwind and during poor visibility. The Arkona Basin is currently the focus of large-scale offshore wind farm development activities with a full built out of the region’s capacity for offshore wind projected to cover approximately 80% of the migration corridor. Our results indicate that the overall collision risk of migrating cranes will depend on the frequency of adverse conditions which cause the birds to fly at rotor height over the wind development zone. Flight altitude of common cranes ( Grus grus ) crossing the Arkona Basin (Baltic Sea): implications for offshore wind farm development Henrik Skov 1 *, Stefan Heinänen 1,2 , Lars O. Mortensen 1 , Johan Månsson 3 , Lovisa Nilsson 3 , Rune S. Tjørnløv 1,4 and Ramunas Zydelis 1,5 1 DHI, Agern Alle 5, 2970 Hørsholm, Denmark 2 NOVIA, University of Applied Sciences, Hämeenkatu 13, Gripen, 2nd Floor, F-20500 Turku, Finland 3 Swedish University of Agricultural Sciences, Department of Ecology, 739 93 Riddarhyttan, Sweden 4 WSP, Linnes Alle 2, 2630 Taastrup, Denmark 5 Ornitela, UAB, Švitrigailos g. 11K–109, LT-03228 Vilnius, Lithuania Correspondence: Henrik Skov ( [email protected] ) Abstract The common crane (Grus grus ), like other soaring species of birds, uses a migration strategy to minimise the risk of wind drift over open sea, resulting in aggregation of birds along migratory corridors. With the planned large-scale development of offshore wind farms there is a need for an improved understanding of the potential interactions between cranes and the wind turbines as they cross the sea during migration. By using laser rangefinder tracking and GPS-tagged crane individuals we studied the vertical flight behaviour in relation to weather conditions as they cross the Arkona Basin between Sweden and Germany. The effect of weather conditions on the vertical distribution (i.e. flight altitudes) of the cranes was modelled using generalized additive mixed models. The results show that the flight altitude of common cranes crossing the basin strongly depends on the wind and visibility conditions. Both during the spring and autumn migration the cranes utilise thermal winds at the coast to soar, and frequently reach altitudes >300 m. Despite variability in wind and visibility conditions, the model predictions showed that the flight altitude descended towards the central offshore parts of the basin with a steeper descending trend during headwind and during poor visibility. The Arkona Basin is currently the focus of large-scale offshore wind farm development activities with a full built out of the region’s capacity for offshore wind projected to cover approximately 80% of the migration corridor. Our results indicate that the overall collision risk of migrating cranes will depend on the frequency of adverse conditions which cause the birds to fly at rotor height over the wind development zone. Keywords: Grus grus, long-distance migration, flight altitude over sea, weather influence on flight profile Introduction Development of wind energy is a key component of the strategies to reduce greenhouse gas emissions (WindEurope 2023). However, the expansion of wind energy may have detrimental effects on biodiversity and one of the main impacts is lethal collisions of birds (Thaxter et al. 2017). The lower potential for soaring over open sea may force soaring migrants to fly at lower altitude. As (low) flight altitude constitutes an important element of bird collision risk with wind energy installations, soaring species may be exposed to a higher risk of collision with wind energy development offshore. Yet, detailed studies of the migratory behaviour of soaring species are currently missing from areas targeted for offshore wind development. Many species of soaring birds migrate in large, spatiotemporally aggregated flocks due to their strong avoidance of crossing large expanses of open water (Kerlinger 1989, Leshem and Yom-Tov 1996). The avoidance of open sea areas during long-distance migration may be managed by migration strategies to both mitigate the risk of wind drift over open sea during cross wind conditions (Alerstam and Bauer 1973, Alerstam 1975) and of lowering flight altitude due to the lack of thermals offshore (Newton 2008). Thermal convection dynamics are known to strongly influence the flight altitudes of soaring species (Leshem and Yom-Tov 1996, Shannon et al. 2002, Shamoun-Baranes et al. 2003). Thermals may provide energy-free lifts, but the occurrence is considered to be relatively low at sea (Newton 2008). However, recent studies have indicated soaring birds may find suitable migratory corridors over large expanses of open sea under specific wind conditions, when being able to exploit localised thermals (Duriez et al. 2018, Nourani et al. 2018, Pekarsky et al. 2024) combined with wind support (Nourani et al. 2021, Škrábal et al. 2023) offshore. A recent study of GPS-tagged red kite (Milvus milvus) showed that although such conditions may occur offshore, higher frequency of flapping flights, lower flying altitudes, and climb rates are typical offshore (Škrábal et al. 2023). Along the same lines, Pekarsky et al. 2024 found that Common Crane (Grus grus ) when crossing the Black Sea use thermal convection cells created by outbreaks of cold air over warm seawater which appear at a low frequency. Common crane (hereafter crane) is a short to long-term migrant using thermal winds and soaring during migration (Alerstam and Bauer 1973, Alerstam 1975). The migration strategy of the cranes leads to a funnelling effect along well-established migratory corridors like the Arkona Basin where the cross-sea distance between Sweden and Germany is the shortest. Hence, the Arkona basin constitutes the main migratory corridor for the common cranes migrating between wintering grounds in Southwest Europe and breeding grounds in Sweden and Norway (Swanberg 1985). The crane is long-lived with a high annual survival rate (0.85; Bautista and Alonso 2021). Crane populations in northern Europe have shown an increasing trend at least over the past 27 years; 0.84% per year from 1988-2012 and 2.43% per year from 2003-2012 (Wetlands International 2016). The population in Sweden is estimated to have increased by 4 % annually since 1997 but has stabilised after 2005. When crossing the Arkona basin, the cranes use the thermal uplifts occurring near the coast to gain altitude before crossing the basin (Mortensen et al. 2020). However, due to lack of data from the offshore parts of the region little is documented on the ability for common cranes to capitalise on favourable wind conditions and local thermals as they cross the 100-130 km wide open sea of the Arkona Basin. The Arkona basin in the western Baltic Sea is currently the focus of large-scale offshore wind farm development with projected wind farms covering 80% of the migration corridor used by cranes (List of offshore wind farms in the Baltic Sea - Wikipedia). In order to test to what extent migrating cranes may be expected to fly at lower altitudes offshore, our study focused on investigating how the flight altitude varies with weather conditions (wind direction and visibility) and distance to shore in the Arkona Basin. As nearly the entire Swedish and Norwegian population of cranes crosses the Arkona Basin during migration (Swanberg 1985, Hansson et al. 2024), and given the accessibility of the coastal areas in Sweden, Germany and Denmark), the region provides an optimal setting for detailed investigation of cranes’ flight altitude profiles. The possibility to collect a large sample size on all three coasts as well as offshore would enable us to assess the dynamics of flight altitudes across a wide range of wind and visibility conditions and validate the assumptions concerning elevated collision risk offshore. Hence, the results were anticipated to improve assessments of the potential interactions between soaring migrants and future offshore wind energy installations. Material and methods 2.1 Study area The Arkona basin is located in the western Baltic Sea, between the German, Danish and Swedish coasts, north of the island Rügen (Figure 1). The region typically experiences mild winters with temperatures around 0° C, and cool summers. The prevailing winds during spring and autumn are from the west and southwest in the area. During autumn, cranes leave the southern part of mainland Sweden and cross the Arkona Basin aiming for Rügen where they usually stop-over before continuing south. The Swedish and Norwegian populations (including juveniles) which pass the Arkona Basin is estimated at 84,000 individuals (Wetlands International 2016), and they mainly cross the region between Bornholm and Falster over a broad front both during spring and autumn. Following energy fuelling periods at autumn and spring staging sites, cranes generally depart from Sweden between mid-September and mid-October, and from Rügen, Germany between mid-March and mid-April followed by the crossing of the Arkona Basin. Figure 1 Overview of study area in the Arkona Basin. Location of data collection sites at Falsterbo, Bornholm, Fino 2 and Falster is indicated 2.2 Flight altitude Flight altitude data of migrating cranes were collected by visual tracking using laser range finders and satellite tracking data derived from GPS-tagged individuals. 2.2.1 Laser rangefinder Laser rangefinder tracking of migrating common crane was carried out to collect 3-D flight data from the FINO-2 research platform in the German part of Krieger’s Flak located 40 km from the coasts of Germany and Sweden as well as from the coasts of Denmark and Sweden (Skov et al. 2015, Figure 1, Table 1). Table 1. Overview of rangefinder tracking of Common Cranes September 3. - October 16. 2013 FINO-2 platform Lat 55°01 / Long 13°15 March 31. – April 21. 2013 and October 11-12. 2013 Falsterbo Reef Lighthouse Lat 55°19 / Long 12°40 April 1. - May 24. 2013 and October 2. - October 11. 2013 Coasts of eastern Denmark Lat 54°92 / Long 12°56 September 23. 2014 Bornholm Lat 55°12 / Long 14°74 March 31. - May 12. 2013 and September 20. - September 24. 2013 Coasts of southern Sweden Lat 55°31 / Long 13°31 Laser rangefinders of the type Vectronix 21 Aero were used to collect species-specific 3-D data on migrating cranes. The laser rangefinder is equipped with a build-in, battery driven laser system, that allows recordings of distance, altitude and direction to a given object. Thus, operated at known geographical positions and elevations, the laser rangefinders can be used to obtain three-dimensional data on migrating birds. Under optimal conditions, laser rangefinders can be used up to approx. 3 km for the largest bird species, depending on the angle of view and bird flight behaviour (i.e., gliding, soaring or flapping). Laser rangefinders can be operated with approximately 10-15 second intervals, with automatically GPS-logged positions and altitudes providing long series of recordings for an individual bird or flock. The metal constructions on the FINO-2 platform and the Falsterbo light house caused distortion of the collected GPS-data by the rangefinder, which may have interfered with the geo-positioning of the recorded rangefinder data. To account for this, calibration data was collected regularly and used to spatially adjust the locations. 2.2.2 Satellite -tracking Satellite-tracking data were derived from eleven GPS-tagged cranes. The tagging of juvenile cranes was undertaken at breeding sites in southcentral (Lat 59°73, Long 15°48) and southwestern (Lat 57°49, Long 13°35) Sweden during July 2013. Pre-fledged juveniles were caught by short distance runs and transmitters were attached using flexible harnesses (see Månsson et al. 2013 for more details about capture and tagging). As the juvenile cranes follow the parents during the first autumn migration the GPS tracks reflect the overall migration paths of the family group. The common cranes were tagged with ARGOS GPS / GSM transmitters (weight 80 grams) powered by solar panels. Transmitters recorded GPS positions at 15-30 minutes intervals during daylight hours. The transmitters had a pre-set geofence encircling the southern open sea part of the Baltic Sea, within which GPS positions were collected every 30 seconds. In addition to recording geographic locations as longitude and latitude, the transmitter GPS module also logged altitude, speed over ground and movement direction. The tagging procedure was approved by the Animal Ethics Committee of central Sweden (C104/10, C53/13). 2.3 Meteorological data The weather data were extracted from the regional weather model by StormGeo (www.storm.no), to relate obtained satellite and rangefinder tracks to spatiotemporal explicit weather conditions .The regional model is based on the global weather model run by the European Centre for Medium-Range Weather Forecasts (ECMWF) | Advancing global NWP through international collaboration). The spatial resolution of the WRF model is 0.1 x 0.1 degree, and the temporal resolution is one hour. Meteorological data for each observation or GPS location were extracted, using the date/time and latitude/longitude of each observation. Meteorological variables included precipitation (mm), clearness (%), humidity (%), air pressure (hPa), wind speed (m/s) and wind direction (degrees). We calculated the relative wind direction for the cranes, which were categorized into four equally distributed (90°) wind classes (head wind, tail wind, left cross wind and right cross wind). 2.4 Data handling Satellite tracking data underwent some basic filtering. Several GPS positions with erroneous altitude measurements were filtered manually by removing altitudes < 0 m, and measurements that were clearly unrealistic considering the fine temporal resolution of the dataset, i.e. records showing clear spikes when having altitude plotted along time axis. Distance to land in meters was calculated for each observation. 2.5 Vertical distribution modelling The vertical distribution of common cranes during migration across the Arkona basin was modelled by studying the effect of meteorological conditions on the flight altitudes. As relationships were expected to be non-linear with data having non-normal distributed errors, we used the semi-parametric and data driven generalized additive mixed modelling approach (GAMMs, Wood 2006, Zuur et al. 2009). This also enabled us to account for the spatial and temporal autocorrelation (non-independencies in the residuals) in the data. With flight altitude as dependent variable, we included distance to land (meters), wind speed (m/s) and clearness as smooth functions (k = 5). Relative wind direction was added as a factorial variable, where the wind was classified as either head, tail, left or right sided. To account for the temporal autocorrelation in the data we included the season (spring/autumn) as a random term and a first order autocorrelation structure, corAR1, grouped by the individual tracks. The model was fitted with a gamma distribution (with log a link) The predictive accuracy of the models was evaluated by using a split sample approach, fitting the model on 70% of the tracks and evaluating the models on the remaining 30%. The agreement between the observed and predicted altitudes was tested using the Spearman’s rank correlation coefficient. The model fit was also assessed by the adjusted R-square values (variance explained) and an inspection of the residuals. The GAMM models were fitted using the “mgcv” package (Wood, 2006) in R (version 2.13.0,R Development Core Team 2004) and Results 3.1 Migration intensity of common crane The vast majority of directions recorded by rangefinder from Falsterbo were concentrated around S in the direction of Rügen (Figure 2). During spring, the mean direction of migrating cranes were 13°, and 185° during autumn. Figure 2 Sampled migration directions of common cranes at Falsterbo, 20-24 September 2013 (Skov et al. 2015). Numbers on the Y-axes refer to sample size (number of recordings by laser rangefinder). Sample size refers to the number of individuals, albeit they typically occurred in flocks. Each wedge represents a sector of 15°. The mean direction is indicated by the black line running from the centre of the graph to the outer edge. The arcs extending to either side represent the 95% confidence limits of the mean direction. 3.2 Flight altitude distribution of common crane The patterns of flight altitude of migrating cranes recorded by rangefinder show that the birds cross the Arkona Basin at variable altitudes from a few metres to more than 200 m above sea surface (Figure 3). The general descend in flight altitude from the Swedish coast in autumn is nonetheless very clear (Figure 3). The satellite tracking data confirmed the patterns recorded by direct observation (Figure 4). The crossing of approximately 80 km of open water took about 1-2 hours, depending on weather conditions. Three satellite tracks were obtained during spring (Figure 4). One bird was able to increase altitude to more than 600m over a well-defined shorter distance off the German coast and then continued towards Sweden below 200m. The two other cranes displayed more distinct descends from the German coast to the offshore parts of the region. One of the birds descended to altitudes between 50m and 250m, while the other bird descended to below 50m before reaching the Swedish coast and ascended to 250m (Figure 4). During autumn, four of the satellite tracked birds displayed clear descends in altitude from the Swedish coast, yet the angle of descend varied greatly between tracks and days. Two tracks crossed the entire open sea area at 175m altitude and displayed a slight increase in altitude off the German coast (Figure 4). One tracked individual flew just a few meters above water level all the way when crossing the Baltic. Figure 3 Frequency distribution of altitude measurements of common crane by laser rangefinder at the Swedish and the Danish coast and at the FINO-2 platform, see Table 1. Figure 4 Altitude measurements of 11 GPS-tagged common crane 2013-2014. The location of the Arkona Basin is indicated by the shaded area. The predictive accuracy of the GAMM was high, with a good agreement between observed and predicted altitudes and a Spearman’s rank correlation of 0.40 and an adjusted R2 of 0.35. The model fit can be regarded as good as we were able to account for the strong temporal and spatial autocorrelation in the track data by using the correlation structure and random term. Based on the confidence intervals, the model was best at predicting intermediate flight altitudes, whereas predictions at very high or low altitudes were less precise (Figure 5). We used the model for predicting the average seasonal flight altitude during average, poor and good visibility and during tail, head and cross winds. According to the predictions the common cranes descend in altitude after leaving the coast of Germany and Sweden and fly higher in tail winds and clearer weather (Figure 5). During spring, except for during optimal conditions with tail wind and good visibility the model shows that most common crane fly below 300 m when they cross Arkona basin (Figure 6). During autumn, although optimal conditions may enable birds to soar to altitudes above 700m before leaving the coast of Sweden they generally descend to altitudes below 300 m over the central parts of the Arkona Basin. Figure 5 GAMM response curves for the common crane flight altitudes based on satellite tracking and rangefinder data from both spring and autumn collected in the Arkona Basin 2013-2014. The values of the environmental predictors are shown on the X-axis. The response (flight altitude) on the Y-axis is on the scale of the linear predictor, which means that the y-axis reflects the contribution of each predictor to the overall linear predictor, rather than the actual predicted values of the response variable. The degree of smoothing is indicated in the title of the Y-axis. The shaded areas and the dotted lines show the 95% Bayesian confidence intervals. The four wind classes (WC) in the bottom right graphic are 1: headwind, 2: easterly crosswind, 3: westerly crosswind, 4: headwind. Discussion As the first study of the flight altitude of cranes during seasonal migrations across the Baltic Sea, we have shown how cranes may capitalise on favourable wind conditions and local offshore thermals. Although the occurrence of thermals that can provide energy-free lifts is relatively low at sea (Newton 2008), soaring species like cranes may find suitable migratory corridors over large expanses of open sea (Nourani et al. 2018, 2021) and may even be able to exploit localised thermals and wind support offshore (Duriez et al. 2018, Škrábal et al. (2023), Pekarsky et al. (2024). Yet, detailed studies of the migratory behaviour of cranes have been missing from sea areas targeted for offshore wind development. Our results from both the satellite tracking and the rangefinder data corroborate earlier findings that the cranes use the thermal uplifts occurring near the coast to gain altitude before crossing the Arkona Basin (Mortensen et al. 2020). However, the results provided evidence that that the flight altitude of cranes crossing the basin strongly depends on the wind conditions and visibility. Both during the spring and autumn migration the cranes utilise thermals at the coast to soar to altitudes which frequently reach >300 m. Despite variability in wind and visibility conditions, the model predictions showed that the mean flight altitude profiles over the basin descended to altitudes below 250 m towards the central offshore parts with a steeper descending trend during headwind and during poor visibility. Despite the general flight altitude patterns, isolated instances of cranes ascending to altitudes above 250 m were observed near the German and Swedish coasts. These events were recorded by two GPS-tagged individuals during both spring and autumn migration. These two events suggest that cranes may use localized thermals and/or wind support when crossing the Baltic Sea, similar behaviour has been observed in ospreys (Pandion haliaetus) crossing the Mediterranean Sea (Duriez et al. 2018), in red kites crossing the Adriatic Sea in Škrábal et al. (2023) and in cranes passing the Black Sea (Pekarsky et al. 2024). Further studies are recommended to clarify the extent to which cranes utilise localized thermals, horizontal wind support or both during such events. As the flight altitude of cranes changes significantly with weather conditions the probability for interaction and potential collision with offshore wind energy development will most likely vary in the Arkona Basin. Arkona Basin is currently the focus of large-scale offshore wind farm development with a total of 27 commissioned, consented and planned offshore wind projects over the next couple of decades (https://map.4coffshore.com/offshorewind). As the future 12 MW+ wind turbines deployed in the Arkona Basin will be at least 250 m high, the overall collision mortality will depend on the frequency of adverse conditions which cause the birds to fly at or below 250 m. Despite the weather-induced variations in the flight altitude, these behavioural investigations clearly indicate that the vast majority of cranes will cross the Arkona Basin at altitudes between 50 and 250 m. Accordingly, although cranes may find suitable migration conditions over the open water parts of the Arkona Basin lower flying altitudes and lower climb rates as compared to the coastal areas are to be expected as a function of the lower strength and abundance of thermals offshore (Škrábal et al. 2023). Figure 6 Average predicted altitude for common crane in relation to distance from the coast of Sweden during autumn and from the coast of Germany during spring in different visibility and wind directions as compared to the height of planned wind turbines. All other predictor variables are set to mean values. The coloured lines indicate the predicted flight altitudes, and the red and blue rectangles indicate the rotor swept area by 15 MW wind turbines planned in the central part of the region. Author contributions Henrik Skov: Conceptualization (lead), Funding acquisition (lead), Methodology (equal), Project administration (lead), Writing – review and edit­ing (equal). Lars O. Mortensen: Methodology (equal), Statistical analysis (equal), Writing – original draft (lead), Writing – review and edit­ing (equal). Stefan Heinänen: Methodology (equal), Investigation (equal), Statistical analysis (equal). Rune S. Tjørnløv: Statistical analysis (equal). Ramunas Zydelis: Methodology (equal), Investigation (equal), Statistical analysis (equal). Johan Månsson: Investigation (equal), Writing – review and edit­ing (equal), Lovisa Nilsson : Investigation (equal), Writing – review and edit­ing (equal). Acknowledgements We thank members of Tranemogruppen, Sweden and students and staff of the Swedish University of Agricultural Sciences (SLU) as well as Mark Desholm, Århus University for their help in monitoring breeding cranes and capturing juveniles for transmitter deployment. The crane telemetry program and baseline investigations for the Kriegers Flak project were funded by EnergiNet.dk. The follow-up assessments for the development of offshore wind in the Danish part of the Baltic Sea was funded by the Danish Energy Agency. Conflict of interest The authors declare no conflicts of interest. Data availability statement The information presented in this article provides only a generic overview of the collected material. The dataset is posted on a public animal tracking portal www.movebank.org under the name “GPS telemetry of Common Cranes, Sweden”. References Alerstam, T. 1975. Crane Grus grus migration over sea and land. - Ibis 117: 489-495. Alerstam, T. and Bauer, C,-A. 1973. A radar study of the spring migration of the Crane (Grus grus) over the southern Baltic area. - Vogelwarte 27: 1-16. Bautista, L.M. and Alonso, J.C. 2021. What do we know about survival of Common cranes? An elementary introduction with EURING databank. Proceedings of the European Crane Conference, 9:76-80. Dulau, P. (ed.). Conference organized by Syndicat Mixte de Gestion des Milieux Naturels – Réserve Nationale de Faune Sauvage d’Arjuzanx, 3rd December 2018. Arjuzanx, France. Duriez, O., Peron, G., Gremillet, D., Sforzi, A. and Monti, F. 2018. Migrating ospreys use thermal uplift over the open sea. - Biol Lett. 14:20180687. Hansson, P., Nilsson, L., Lundgren, S., Skyllberg, U., Sandvik, J., & Månsson, J. 2024. Flyways of Common Cranes Grus grus breeding in Fennoscandia. - Ornis Svecica 34: 155–170. tps://doi.org/10.34080/os.v34.23602 Kerlinger, P. 1989. Flight strategies of migrating hawks. - University of Chicago Press, Chicago. Leshem Y and Yom-Tov Y. 1996. The use of thermals by soaring migrants. - Ibis 138: 667–674. (doi:10.1111/j.1474-919X.1996.tb04768.x) Mortensen, L.O., Skov, H., Tjørnløv, R.S. and Tuhuteru, N. 2020. Assessment of areas for development of offshore wind farms on Rønne Bank in relation to birds. - DHI Report. Commissioned by the Danish Energy Agency. Månsson J., Nilsson L. and Hake M. 2013. Territory size and habitat selection of breeding common cranes in a boreal landscape. - Ornis Fennica 90: 65–72. Newton I. 2008. The migration ecology of birds. - Academic Press, London. Nourani, E., Safi, K., Yamaguchi, N.M. and Higuchi, H. 2018. Raptor migration in an oceanic flyway: wind and geography shape the migratory route of grey-faced buzzards in East Asia. - R Soc Open Sci. 5: 171555. Nourani, E., Bohrer, G., Becciu, P., Bierregaard, R.O., Duriez, O., Figuerola, J., Gangoso, L., Giokas, S., Higuchi, H., Kassara, C., Kulikova, O., Lecomte, N., Monti, F., Pokrovsky, I., Sforzi, A., Therrien, J.-F., Tsiopelas, N., Vansteelant, W.M. G., Viana, D.S., Yamaguchi, N.M., Wikelski, M. and Safi, K. 2021. The interplay of wind and uplift facilitates over-water flight in facultative soaring birds. - Proc R Soc B Biol Sci. 288:20211603. Pekarsky, S., Shohami, D., Horvitz, N., Bowie, R.C.K., Kamath, P.L., Markin, Y., Getz, W.M., Nathan, R. 2024. Cranes soar on thermal updrafts behind cold fronts as they migrate across the sea. Proc. R. Soc. B 291: 20231243. https://doi.org/10.1098/rspb.2023.1243 R Development Core Team. 2004. A Language and Environment for Statistical Computing. - R Foundation for Statistical Computing, Vienna, Austria. http://www.Rproject. org. Shamoun-Baranes, J., Baharad, A., Alpert, P., Berthold, P., Yom-Tov, Y., Dvir, Y., and Leshem, Y. 2003. The effect of wind, season and latitude on the migration speed of white storks Ciconia ciconia, along the eastern migration route. - Journal of Avian Biology 34: 97–104. https ://doi.org/10.1034/j.1600- 048X.2003.03079.x Shannon, H. D., Young, G. S., Yates, M. A., Fuller, M. R. and Seegar, W. S. 2002. Measurements of thermal updraft intensity over complex terrain using American white pelicans and a simple boundary-layer forecast model. - Bound.-Layer Meteor. 104: 167–199. Skov, H., Desholm, M., Heinänen, S., Johansen, T.W. and Therkildsen, O.R. 2015. Kriegers Flak Offshore Wind Farm. Environmental Impact Assessment. - DHI Technical background report. Birds and bats. Commissioned by EnergiNet.dk. Skov, H., Desholm, M., Heinänen, S., Kahlert, J.A., Laubek, B., Jensen, N.E., Žydelis, R. and Jensen, B.P. 2016. Patterns of migrating soaring migrants indicate attraction to marine wind farms. - Biol. Lett. 12: 20160804. http://dx.doi.org/10.1098/rsbl.2016.0804 Škrábal, J., Krejčí, Š., Raab, R., Sebastián-González, E. and Literák I. S. 2023. Soaring over open waters: horizontal winds provide lift to soaring migrants in weak thermal conditions. - Mov Ecol 11: 76. https://doi.org/10.1186/s40462-023-00438-6 Swanberg, P.O. 1987. Migration routes of Swedish cranes ( Grus grus ) present knowledge. - Aquila 93/94: 63-73. Thaxter, C., Buchanan, G.M., Carr, J., Butchart, S., Newbold, T., Green, R., Tobias, J.A., Foden, W.B., O’Brien, S. and Pearce-Higgins, J.W. 2017. Bird and bat species’ global vulnerability to collision mortality at wind farms revealed through a trait-based assessment. Proc. R. Soc. B.28420170829. http://doi.org/10.1098/rspb.2017.0829 Wetlands International. 2016. ”Waterbird Population Estimates”. Retrieved from wpe.wetlands.org on Saturday 11 Jan 2025. Wind Energy in Europe. 2023. 2022 Statistics and the Outlook for 2023–2027. WindEurope, Brussels, Belgium. Wood, S. N. 2006. Generalized Additive Models: An Introduction with R. - Chapman and Hall, London, UK. Zuur, A.F., Leno, E.N., Walker, N., Saveliev, A.A. and Smith, G.M. 2009. Mixed Effects Models and Extensions in Ecology with R. - Springer, Berlin, 524 pp. Supplementary Material File (image4.emf) Download 83.00 KB File (image5.emf) Download 56.10 KB Information & Authors Information Version history V1 Version 1 03 September 2025 Peer review timeline Published Ecology and Evolution Version of Record 12 Dec 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Ecology and Evolution Keywords behavioral ecology description multiple vertebrate Authors Affiliations Henrik Skov 0000-0001-8835-3166 [email protected] DHI View all articles by this author Stefan Heinänen Novia University of Applied Sciences - Campus Åbo View all articles by this author Lars O. Mortensen 0000-0002-8879-1382 DHI View all articles by this author Johan Månsson 0000-0002-5189-2091 Swedish University of Agricultural Sciences Faculty of Natural Resources and Agricultural Sciences View all articles by this author Lovisa Nilsson 0000-0003-4822-7864 Swedish University of Agricultural Sciences View all articles by this author Rune Tjørnløv WSP - Denmark View all articles by this author Ramūnas Žydelis Ornitela UAB View all articles by this author Metrics & Citations Metrics Article Usage 322 views 167 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Henrik Skov, Stefan Heinänen, Lars O. Mortensen, et al. Flight altitude of common cranes (Grus grus) crossing the Arkona Basin (Baltic Sea): implications for offshore wind farm development. Authorea . 03 September 2025. DOI: https://doi.org/10.22541/au.175692142.22513960/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/au.175692142.22513960/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fecca664bc109d6',t:'MTc3OTI5NTMwNA=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();