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Article

Do Seabirds Control Wind Drift during Their Migration across the Strait of Gibraltar? A Study Using Remote Tracking by Radar

by
Gonzalo Muñoz Arroyo
1,2,* and
María Mateos-Rodríguez
3
1
Institute of Marine Research (INMAR), Cádiz University, 11510 Cádiz, Spain
2
Biology Department, Faculty of Marine and Environmental Sciences, University of Cadiz, Av. Republica Saharaui, s/n, Puerto Real, 11510 Cádiz, Spain
3
Natural Sciences Department, Eulogio Florentino Sanz High School, Av. Emilio Romero 22, Arevalo, 05200 Ávila, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2022, 14(12), 2792; https://doi.org/10.3390/rs14122792
Submission received: 26 April 2022 / Revised: 2 June 2022 / Accepted: 3 June 2022 / Published: 10 June 2022
(This article belongs to the Special Issue Monitoring Bird Movements by Remote Sensing)
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Abstract

:
This study presents data on the directional flying behaviour of the five most abundant seabird species migrating across the Strait of Gibraltar in relation to the wind, as observed from the north coast, based on radar tracking, and identified to species level by visual observations. A total of 318 seabird trajectories were analysed, illustrating the expected east–west or west–east movements in spring and autumn. We hypothesised that the seabirds that cross the Strait channel during their migrations would behave differently with respect to compensation for wind direction, depending on their flight styles, the migratory period, and the prevailing winds. In this regard, our results showed that flapping birds (Razorbill, Puffin, Northern Gannet, and Balearic shearwater) compensated for wind drift independently of the season and the predominant wind direction. This agrees with the theory that suggests that under moderate winds and whenever visual contact with the coastline is present (as in the case of our study), migrants should compensate for wind drift to avoid being drifted towards the coast, off their main direction of flight. However, Cory’s shearwater, an active gliding seabird with long, slender wings, showed an adaptive directional response to wind, allowing it to be drifted in spring when westerly tailwinds were prevalent, but compensated for wind in autumn, when both easterly and westerly winds were similarly frequent. This adaptive flight behaviour allows it to take advantage of the prevailing tailwinds in spring, gaining ground speed and saving energy during its passage through the Strait, while in autumn, more frequent headwind conditions and a more directional migration to the south may favour compensating for wind drift. Our results support the usefulness of bird radar as a remote tool for describing the pattern of animal movements in the marine environment, as well as their behavioural response to atmospheric conditions. These studies are particularly relevant in the current framework of climate change.

Graphical Abstract

1. Introduction

Flight performance is one of the main evolutionary traits of migratory birds. Describing flight patterns and behaviour can be challenging, especially for birds that undertake migratory routes through remote and inaccessible areas, such as pelagic seabirds. Recent GPS tracking studies have shown how global winds affect long-distance patterns of foraging and migration behaviour [1,2,3]. However, how these global movement patterns interact with local wind conditions and how they affect flight behaviour is still poorly understood [4]. Radar tracking can provide a better understanding of fine-scale bird flight responses to local conditions.
The wind is an important selective agent in bird migration [5,6], influencing the direction, altitude, speed, and economy of flight [7,8,9]. The resulting path over the ground of a flying bird depends not only on the bird’s own flight direction (direction of body axis) and speed but also on wind direction and speed. Birds may, at times, fly in winds that would take them from their preferred direction of flight. Under these conditions, birds may allow being totally drifted or compensate for wind drift. In this sense, ‘wind drift compensation’ is typically understood as the adjustment of the heading so that the track taken is oriented towards the goal [10]. Depending on the species and their environmental and ecological situations, total drift, partial drift, compensation, or overcompensation can be predicted to be adaptive [5,11,12,13,14,15].
This variability of birds’ behaviour in relation to winds in different situations is probably the result of constraints in their capacity for wind compensation under certain conditions as well as of adaptive variation in their responses to wind [16,17]. Birds are assumed to possess the ability to fully compensate for wind drift when they have access to visual contact with the ground [10]. However, when flying over moving surfaces such as clouds, birds will not be able to prevent wind drift by orienting themselves with respect to a fixed landscape and will, therefore, be subjected to drift [18]. There is also a limit to strong wind speed where birds will be overpowered by the winds and unable to avoid drifting off their preferred track direction [15]. Nonetheless, under moderate winds, birds should be able to compensate for wind drift [5].
Being drifted by the wind can be beneficial in certain circumstances. Wind drift allows higher ground speed, reducing flight cost. Thus, some migratory birds may use an adaptive drift strategy, consisting of drift in high wind speed conditions or during the beginning of their migratory journey, combined with compensation in lower wind speeds or during later stages as they approach their destinations [19,20].
Given the great importance of wind for the economy and the precision of bird migration, it seems reasonable to assume that birds have evolved a high degree of flexibility in their orientation response to wind. A number of studies provide supporting evidence for such adaptive drift or compensation behaviours [10,21]. However, studies on seabirds are scarce, despite the fact that many seabirds undertake long transoceanic migrations, during which they show a high range of flight styles, from continuous flapping to dynamic soaring [22]. In some studies in the Artic [23,24,25], tracking radars were used to analyse bird flight directions (seabirds, among others) in relation to wind, but species corresponding to radar tracks could not be discriminated. Other studies do not cover migratory flights but rather foraging trips [3,26]. Therefore, comparative studies on how migrating seabirds behave with respect to wind using different flight strategies at the local level are lacking.
In this study, we investigate the response to local wind conditions—in terms of wind compensation and drift—of the five most abundant seabirds crossing the Strait of Gibraltar in spring and autumn migrations. For this purpose, flying seabird tracks were recorded by a horizontally scanning ship navigation radar and simultaneously identified at the species level by visual observation. A combination of radar tracking and visual observation has been previously tested as an effective method, providing reliable results [16,27]. The following hypotheses are tested: (a) seabirds migrating across the Strait of Gibraltar mostly tend to compensate for wind drift because visual landmarks are easily accessible when flying along this migratory bottleneck; (b) seabirds behave differently with respect to compensation for wind direction according to their flight styles, with flapping birds completely compensating for wind drift to avoid being diverted from their preferred direction, while active gliding birds are at least partly drifted to take advantage of favourable wind conditions.

2. Materials and Methods

The study was carried out in the spring and autumn of 2006 in the Strait of Gibraltar, one of the hot spots for bird migration in Europe. This bottleneck is the only marine connection between the Atlantic Ocean and the Mediterranean Sea. Thus, the study covers most seabird populations moving in or out of the Mediterranean Sea throughout the annual cycle [28,29].
In this area, flight trajectories of migrating seabirds were mapped using an S-band surveillance radar (FURUNO FR-2137SBB, peak power output 30 kW, variable pulse 0.07–1.0 µs, transmitting on 3050 MHz), located on a platform 10 m above sea level (a.s.l.) at Tarifa Island (SW Spain, 36°00′2.96″N, 05°36′36.51″W), the southernmost point of the European mainland (Figure 1). This device has shown to be effective in recording the trajectories of selected targets on plan position indicators (PPI, showing the tracks of birds on map-like screens [30]) when no height information is needed, as in the case of low flying seabirds. Data were collected in spring (16 days between 8 March and 1 June) and autumn (12 days between 17 October and 8 November), representing the known phenology of seabird migration in the area [28,29] (Figure 1). All observations were recorded in good weather conditions and under light to moderate winds, below 15.8 m s−1 (see below). Higher wind speeds prevented radar detection of birds due to sea clutter (disturbing wave echoes). Data were simultaneously collected by a radar operator and a visual observer in communication by radio. The observer identified the species and flock size, while the flight path of the identified individual or flock was recorded according to the PPI information in a digital video system. Afterwards, target locations (one every 5 s) were extracted from the recorded images, and subsequently, each location was geographically positioned (see several tracks in Figure 1 as an example). We used geographical information system software to calculate ground speed and track direction for each 5-s interval of the recorded flight paths (ArcView 3.2. [31]). Only tracks lasting more than 30 s were included in the analysis. Hourly wind data recorded at 10 m a.s.l. were obtained from an on-site measuring station located on the tip of Tarifa in an unobstructed position with respect to the prevailing winds. These wind data were used to calculate headings and airspeed.
Track vector (track direction and ground speed) is the result of the sum of the heading vector (heading direction and airspeed) and the wind vector (wind direction and speed). Consequently, airspeed and heading direction can be calculated by vector subtraction of the wind vector from the track vector [32,33].
The airspeeds and heading directions for each 5-s interval were averaged to give the overall mean airspeed and heading direction per track. These overall means are the basis of the present evaluation, and the variation in speed and direction within tracks has not been considered in this paper. Thus, mean vector directions and angular deviations for different samples of tracks were calculated [34].
In this study, directional behaviour was analysed for the five most abundant seabird species passing the Strait during spring and autumn migration. These species are the following: Cory’s shearwater Calonectris diomedea, with long, slender wings, leading to high aspect ratio and low wing loadings, adapted to efficient gliding, being shifted into dynamic soaring under headwinds with certain strength; Balearic shearwater Puffinus mauretanicus has relatively high aspect ratio and low wing loading, but not as extreme as the larger Cory’s shearwater, and therefore, uses flapping more often than the latter; Northern Gannet Morus bassanus has a high aspect ratio, but also a high wing loading and is, therefore, adapted to use mixed flight behaviour, interrupting long flapping phases by relatively short glides; Puffin Fratercula arctica and Razorbill Alca torda are forced to beat their short and narrow wings very fast, showing the fastest flapping rate of the study species (Table 1). Because of the difficulty of identification and the frequent occurrence of mixed flocks, Puffins and Razorbills were considered together as auks. Except for auks (with otherwise similar characteristics), only flocks with individuals of the same species were considered. The migratory flight paths of the considered species and their passage times are given in Figure 1.
To evaluate whether or not migrants compensate for wind drift during flight, directional behaviour is analysed by comparing track and heading directions under different wind conditions. Bird tracks for each species were divided into two groups according to whether winds were coming from the right or the left of the average flight direction of the whole sample [16]. For birds compensating for wind drift, it is expected that the trajectories would be similar for the two groups regardless of where the winds came from, while the headings would differ between groups, being shifted towards the wind (to the right in winds from the right and vice versa). Contrarily, if the birds were drifted by the wind, tracks would be expected to change with the wind, but headings would remain the same irrespective of what direction the wind was coming from.
The relative magnitude of drift and compensation was calculated following [16]. Mean track directions in winds from the left and right are denoted T1 and T2, respectively, and the corresponding mean heading directions are H1 and H2. The difference between track and heading is denoted α, then α1 will be T1 − H1 and α2 will be T2 − H2. The estimated magnitude of drift, Btrack, is then:
Btrack = (T1 − T2/α1 − α2).
With Btrack = 0, there is no drift and complete compensation. If Btrack = 1, there is full drift and no compensation. When 0 < Btrack < 1 there is partial drift and partial compensation. Btrack < 0 corresponded to overcompensation and Btrack > 1 to an overdrift. Similarly, the corresponding magnitude of compensation, Bheading, is:
Bheading = (H1 − H2/α1 − α2)
If Bheading = 0, there is full drift and no compensation. When Bheading = −1, there is full compensation and no drift. Values of Bheading between 0 and −1 indicate partial drift and partial compensation. If Bheading < −1, there is overcompensation and when Bheading > 0, there is overdrift.
Circular statistics were used according to [34]. The Rayleigh test was used to evaluate whether the distribution of flight directions deviated from random. The Watson–Williams test was used to compare flight directions in winds from the left and right. Circular analyses were performed with Oriana v. 2.02e software [37]. Mean ± standard deviations (SD) are presented, with sample size (n).

3. Results

A total of 318 radar tracks of migrating birds were analysed. The total tracking time amounted to 48,545 s (more than 13 h). Tracks lasted between 30 and 490 s (150.1 ± 91.7 s, n = 318). For auks, only prebreeding migration data (towards the Atlantic, Figure 1) were available.
Seabird tracks were recorded under wind conditions ranging from 0–15.8 m s−1 (4.0 ± 2.9 m s−1, n = 318). In spring, winds from the west were predominant (Figure 2, Supplementary Material Table S1). In autumn, there was almost the same number of days with winds from east and west (Figure 2, Supplementary Material Table S1).
Most tracks (74%) were of flocks; the rest corresponded to single birds (Supplementary Material Table S2). The proportion of single birds and maximum flock sizes varied with species: Cory’s shearwater, 9% single, flocks 2–100 birds; Balearic shearwater, 31% single, flocks 2–21 individuals; Northern Gannet, 43% single, flocks 2–10 birds; auks, just once singly, flocks 2–36 individuals (Supplementary Material Table S2).
Track and heading distributions of directions were significantly different from random for all the species and in the two seasons (Rayleigh test; all p < 0.001). Track and heading distributions for all species depended on the season, with the expected west–east movement in autumn and east–west in spring (Figure 2). Birds flying west deviated only slightly from the west (271°–277°), whereas birds flying east showed an east–southeast direction (112°–120°) (Table 2).
In the Strait of Gibraltar, because of its topographical characteristics, the direction of the wind flow is mainly from east and west. As seabirds cross the Strait in an easterly or westerly direction during their migrations, they find mainly opposing or following winds (depending on species and season). During the study period, winds showed this characteristic east–west pattern, but some north or south components also occurred (Figure 2). Seabirds were exposed to crosswinds in 13.2% of the tracks; in the rest of the cases, they were flying with following or opposing winds with partial crosswind component (Supplementary Material Table S2).
Significant differences between heading directions in winds from left and right of the overall mean direction of the sample both in spring and autumn were recorded in all but one case (Cory’s shearwater in spring, Figure 3 and Table 3). The significant differences in heading directions between birds flying in winds from the left and right indicated that, in most cases, seabirds compensate for wind drift (Table 3 and Figure 3). Only Cory’s shearwaters flying east in spring showed partial drift (Table 3 and Figure 3), with very similar headings in winds from left and right (Figure 3). Moreover, the relative magnitude of drift and compensation indicated that virtually total compensation occurred in most species (variations of Btrack or Bheading from 0 and −1 were mostly 0.1–0.2; Table 3). In spring, Cory’s shearwater showed partial wind drift, but because of the small difference of Btrack (0.7) from 1 and of Bheading from 0 (−0.3), it can be considered as not very far from full drift (Table 3).

4. Discussion

4.1. Do Seabirds Compensate for Wind Drift during Their Migrations across the Strait of Gibraltar?

This paper presents directional data for the most abundant species of seabirds migrating across the Strait of Gibraltar under different wind conditions, with the birds identified visually at the species level. Our results showed that flapping seabirds (auks, Gannet, and Balearic shearwater) always compensated for wind drift during their spring and autumn migrations across the Strait of Gibraltar. Cory’s shearwater, a typical gliding bird, also compensated for wind drift in autumn, when there was a similar number of days with winds from east and west, but were drifted by the wind in spring, when they returned to the Mediterranean under prevalent westerly (tail) winds.
The analysis of circular data requires specific statistical methods due to its periodic nature. Whereas some classic analytical tools for circular statistics have been developed [34], they have the disadvantage that it does not allow the addition of covariates [38]. Thus, the assumption of independence of observations by days cannot be tested by adding day as a covariate. However, the track data set used in our study was evenly distributed across different days at different seasons, encompassing a representative range of wind conditions in our study area (with the limitation of strong wind conditions, where our radar could not operate). Therefore, we consider that the effect of this day-dependence, if existing, may be negligible and that our results and conclusions are sound, according to the conditions of the study.
Given the conditions of our study, with migrating seabird species flying at very low altitudes above the sea, under moderate winds, our results agree with the prediction of Alerstam [5], who suggested that generally, birds should compensate for wind drift. In our study, this hypothesis is supported for flapping species, but only partially in the case of gliding species. To compensate for wind drift allows seabirds to avoid the risk of being wind-drifted across the sea and to cross the Strait of Gibraltar in the right direction to keep their migration path. In this sense, birds are assumed to possess the ability to fully compensate for wind drift when they have access to visual contact with the ground [10]. In the Strait of Gibraltar, seabirds are close enough to the coastline to have constant visual land references. Additionally, we showed that seabirds in the Strait of Gibraltar followed paths that were located nearer to the coast than randomly expected [27]. Under these conditions, compensation becomes particularly relevant in order to prevent being drifted over land [39]. Thus, seabirds in the Strait seemed to be able to measure drift by using those landmarks, allowing them to control wind drift and then fully compensate for it. Complete compensation for wind drift has been reported for birds flying along coastlines or other direct leading lines. Bergman [39] described how waterfowls compensate for wind drift during flight along or at least near a coast, in some cases even when flying at high altitude [23] or during the night [40]. Desholm [41], during a radar study of migrating waterfowls (geese and Common Eiders Somateria mollissima) in Denmark, found small deviations from straight-line trajectories that could have resulted from birds repeatedly compensating for wind drift as they travelled towards their goal. He suggested that this is likely a general phenomenon, at least among birds migrating by flapping flight, which is confirmed now with our results with other groups of flapping species.
In our study, different species differed in terms of flocking behaviour. Some authors predict that larger flocks will deviate less from the optimal direction than smaller flocks [42]. Consequently, species flying in more numerous flocks would be expected to differ from single birds or small flocks in terms of flight directionality. However, our study support that compensating for wind drift is a generalised strategy in flapping birds, regardless of their flocking behaviour.
We must stress that, for seabirds migrating thousands of kilometres across the ocean, the Strait of Gibraltar constitutes a very small natural bottleneck that they have to pass at least twice a year within very limited periods. In addition, the range of wind speed conditions that could be covered in our study was restricted to relatively low-intensity winds because of radar constraints in detecting low flying seabirds under high wind conditions [43,44]. Since compensatory or drift behaviour may vary between different situations, depending not only on the wind but also on the destination of the bird’s journey (ref. [10] and references therein), under certain circumstances flapping seabird migrants may allow themselves to be drifted to gain the advantage of a higher ground speed towards their goal [5]. Moreover, under very strong wind conditions, birds can be overpowered by the winds and cannot avoid drifting off their preferred track direction [15]. In our study, the radar capacity to describe bird tracks was constrained to light to moderate winds due to sea clutter, and we could not detect seabirds beyond 15.9 m s−1. Thus, we cannot rule out that this occurs in the Strait of Gibraltar, where strong winds (over 22 m s−1) are not uncommon.

4.2. The Case of a Gliding Species

According to theory [7,10], Cory’s shearwater, an active gliding seabird, fully compensated for wind drift during its postbreeding migration. Nevertheless, this species allows itself to be carried by the wind under moderate winds during spring. This could be due to the prevalence of tailwind conditions in this season, accounting for 79% of tracks of Cory’s shearwater in spring. In autumn, when winds in various directions were similarly distributed, Cory’s shearwater preferred to compensate for them. Therefore, Cory’s shearwaters may prefer to drift when birds experience following winds because there probably is a certain wind angle when birds take optimal advantage of the wind energy, increasing their flight speed and reducing their energy use during a journey through this region. As we predicted in our hypotheses, the capacity to adapt the flight pattern to wind conditions can be constrained by flight type and morphological characteristics of the different species. Mateos-Rodríguez and Bruderer [45], for the same range of species as in our study, showed that these species responded differently to the wind in terms of airspeeds, depending on their morphological characteristics and flight behaviour. In the same way, morphological parameters and flight type could determine seabirds’ directional behaviour. Cory’s shearwater has long, slender wings, leading to a high aspect ratio and low wing loadings, adapted to efficient gliding flight—powered by air currents—by generating low induced drag [22]. These specific characteristics allow it optimises the response to prevalent winds, allowing itself to be drifted even by moderate following winds, thereby increasing its ground speeds. This behaviour, however, is not exhibited by flapping, muscle-driven species. This result makes sense if we consider that, among the five analysed species, Cory’s shearwater is the only gliding species known to take advantage of winds for migration [1,46]. Our result supports those of Felicísimo et al. [46], which maintain that migration flyways followed by shearwaters can result from decisions taken along the route based on the perception of local wind conditions.
Additionally, Cory’s shearwaters in autumn show a directional migration when leaving the Mediterranean following an SW direction leading to the Canary Current system [47], and evidence exists that mass migration of Cory’s shearwater throughout the Strait in autumn seems to occur predominantly along the south coast of the Strait [48] (pers. obs.). Under these conditions, Cory’s shearwaters in autumn can be driven to compensate for gaining a southwest component in their migratory path. In spring, when returning from the central part of the North Atlantic Ocean, Cory’s shearwaters can obtain the advantage of being drifted by prevailing almost purely western winds in order to increase their ground speed and consequently reduce the time to arrive at the breeding colonies. In this sense, we showed a species-dependent pattern of the movements with respect to the distance from the land for seabirds migrating throughout the Strait, with Cory’s shearwaters flying the furthest off the coast from Tarifa [27], which can be advantageous in order to benefit from the wind but also to prevent from being drifted near the coast.

5. Conclusions

Our results support the application of radar studies as remote sensors for describing the pattern of animal movements in the marine environment. In this study, radar revealed how several species of seabirds behaved differently with respect to compensation for wind direction, with gliding species adapting their flight strategy to take advantage of the prevalent winds, whereas flapping species tended to compensate for wind drift independently of the predominant wind direction and season. For seabirds migrating across the open ocean, traversing this migratory bottleneck, only 14 km at its narrowest, under frequent high-wind conditions, forces them to adapt their flight patterns locally to avoid being pushed toward the coastline and to optimise their passage [27,36].
In this sense, the study of animal movement by radars has been instrumental in revealing key influences of the environment on flying migrants [17]. Radar studies have revealed how seabirds develop strategies to optimise their flight, approaching the coast to reduce the effect of headwinds, and moving away with tailwinds, benefiting from increased winds further from the coast [27]. Moreover, radar has been used to describe how birds adjust air speed to wind increment to move faster and reduce the energy cost of flight during migration [42,49]. These results are relevant in the current framework of global change since the expected increase in wind speed over the oceans driven by climate change [50] could impact the behavioural mechanism that shapes migration ecology in pelagic seabirds [4].

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/rs14122792/s1. Table S1. Total number of days in which visual census were carried out by month, season and total (Total days), total days with winds from west (W) and east (E) by month, season and total. Number of tracked seabirds with winds from east and west, by month, season and total (Tracks). Proportion of the total amount of birds visually counted with wind from east and west by month, season and total (Birds). Main direction is referred to the main migration direction in each season depending on the species. Table S2. Radar data for migrating birds identified to species with respect to three categories of flight direction. Number of tracks, number of single birds, and flock size (mean, scatter (s.d. = standard deviation) and range) of migrating bird. Time refers to the total tracking time per species. Three categories of flight directions have been determined according to Spear & Ainley [51]: crosswinds (difference between bird track and wind direction 60° to <120°) and opposing and following winds (difference between bird track and wind direction 0° to <60° and 120° to 180°, respectively).

Author Contributions

Conceptualization, G.M.A. and M.M.-R.; methodology, G.M.A. and M.M.-R.; formal analysis, M.M.-R.; data processing & analysis, M.M.-R.; writing—original draft preparation, G.M.A. and M.M.-R.; writing—review and editing, G.M.A. and M.M.-R.; project administration & funding acquisition, G.M.A. All authors have read and agreed to the published version of the manuscript.

Funding

This study was conducted within a collaboration agreement between the University of Cádiz and the Migres Foundation. The radar facilities were supplied by Ceowind Capital Energy Offshore Company. María Mateos-Rodríguez was granted a FPU fellowship by the Junta de Andalucía.

Acknowledgments

We thank Migres Foundation technical staff for their help in the fieldwork and Bruno Bruderer, Felix Liechti, Juan Ramirez and Andy Paterson for their comments on previous versions of this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Remotesensing 14 02792 g001 550
Figure 1. Migration routes of seabirds crossing the Strait of Gibraltar (birds return along the same routes). Line 1: main prenuptial migration route of auks and Gannet, which pass the Strait of Gibraltar mainly between mid-February to mid-April towards the northern east Atlantic where they breed. They come back to their wintering grounds in the Mediterranean mainly between mid-October to mid-November. Line 2: main postbreeding migration route of Balearic shearwater to the Atlantic Ocean from mid-May to mid-July. This species breeds in the western Mediterranean, where they return mainly between mid-October to mid-November. Line 3: main postbreeding migration route of Cory’s shearwater, mainly between mid-October to mid-November, to their wintering grounds in the sub-Atlantic ocean. This species breeds in the Mediterranean, where they return mainly between mid-February to mid-April (Arroyo et al. [28,29]). Insets: details of the African and Spanish coastline in the area of Tarifa. In the right panel, ten tracks per species (Cory’s shearwater, Balearic shearwater, Northern Gannet, and auks) flying towards the Atlantic are shown as examples of digitised radar images.
Figure 1. Migration routes of seabirds crossing the Strait of Gibraltar (birds return along the same routes). Line 1: main prenuptial migration route of auks and Gannet, which pass the Strait of Gibraltar mainly between mid-February to mid-April towards the northern east Atlantic where they breed. They come back to their wintering grounds in the Mediterranean mainly between mid-October to mid-November. Line 2: main postbreeding migration route of Balearic shearwater to the Atlantic Ocean from mid-May to mid-July. This species breeds in the western Mediterranean, where they return mainly between mid-October to mid-November. Line 3: main postbreeding migration route of Cory’s shearwater, mainly between mid-October to mid-November, to their wintering grounds in the sub-Atlantic ocean. This species breeds in the Mediterranean, where they return mainly between mid-February to mid-April (Arroyo et al. [28,29]). Insets: details of the African and Spanish coastline in the area of Tarifa. In the right panel, ten tracks per species (Cory’s shearwater, Balearic shearwater, Northern Gannet, and auks) flying towards the Atlantic are shown as examples of digitised radar images.
Remotesensing 14 02792 g001
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Figure 2. Total distribution of heading, track, and wind directions, both in spring and autumn migrations. All distributions are bimodal, with peaks in easterly and westerly sectors. Wind direction is the direction the wind is coming from, while flight direction (track and heading) is the direction toward which the bird is moving.
Figure 2. Total distribution of heading, track, and wind directions, both in spring and autumn migrations. All distributions are bimodal, with peaks in easterly and westerly sectors. Wind direction is the direction the wind is coming from, while flight direction (track and heading) is the direction toward which the bird is moving.
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Figure 3. Average track and headings directions, in winds from the left (unbroken bold arrows) and right (broken bold arrows) of the mean direction of each migratory movement. Angular deviations are shown with unbroken lines for flight directions in winds from the left and broken lines for flight directions in winds from the right. n-values given are the total sample sizes and the combined values for both groups together. Mean directions ± angular deviations for each group are given below each panel.
Figure 3. Average track and headings directions, in winds from the left (unbroken bold arrows) and right (broken bold arrows) of the mean direction of each migratory movement. Angular deviations are shown with unbroken lines for flight directions in winds from the left and broken lines for flight directions in winds from the right. n-values given are the total sample sizes and the combined values for both groups together. Mean directions ± angular deviations for each group are given below each panel.
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Table
Table 1. Morphological characteristics (body mass, wingspan, wing area, and aspect ratio) and flight behaviour of the study species are arranged by increasing flapping flight style. Flight styles were categorised from direct observations of the commonest style amongst all individuals observed during migration (unpublished data).
Table 1. Morphological characteristics (body mass, wingspan, wing area, and aspect ratio) and flight behaviour of the study species are arranged by increasing flapping flight style. Flight styles were categorised from direct observations of the commonest style amongst all individuals observed during migration (unpublished data).
SpeciesBody Mass (g)Wing Span (mm)Wing Area (cm2)Wing Loading (Kg m−2)Aspect RatioFight Style
Cory’s S.a946121012307.711.9gliding
Balearic S.b5708406209.211.4flap-gliding
Gannet c30101850262011.513.1flap-gliding
Puffin c39854936910.88.2continuous flapping
Razorbill c62066146213.49.5continuous flapping
a [35]; b [36]; c [22].
Table
Table 2. Radar data for migrating seabirds identified species by different seasons. The number of tracks, mean, and scatter (s.d.—standard deviation, a.d.—angular deviation) of direction (track direction, heading direction and wind direction) of migrating birds, and wind speed. Time refers to the total tracking time per species and season.
Table 2. Radar data for migrating seabirds identified species by different seasons. The number of tracks, mean, and scatter (s.d.—standard deviation, a.d.—angular deviation) of direction (track direction, heading direction and wind direction) of migrating birds, and wind speed. Time refers to the total tracking time per species and season.
SpeciesSeasonN° of TracksTime (s)Track Direction (Degrees)Heading Direction (Degrees)Wind Direction (Degrees)Wind Speed (m/s)
Meana.d.Meana.d.Meana.d.Means.d.
Cory’s shearwaterSpring4310,32511316.411723.228952.75.92.1
Autumn5910,38027122.027625.55794.64.32.5
Balearic shearwaterSpring19228527614.827818.627051.63.63.1
Autumn3036051209.912215.329121.42.31.6
GannetSpring6210,31027812.327715.226840.93.92.0
Autumn53622511411.511412.3173123.72.31.8
AuksSpring5254152778.52789.826291.16.92.8
Table
Table 3. The magnitude of drift and compensation (calculated according to Green and Alerstam [16]) for the comparison between flight directions in winds from the left and right (see text and Figure 3). When the magnitude of drift (Btrack) equals 1, there is full drift, and when it is 0, there is full compensation. Intermediate values indicate partial drift. Similarly, when the magnitude of compensation (Bheading) equals −1, there is full compensation, and when it is 0, there is full drift. Intermediate values indicate partial compensation. Levels of significance for tests of difference between average directions in winds from the left and right: *: p < 0.05, **: p < 0.01, ***: p < 0.001.
Table 3. The magnitude of drift and compensation (calculated according to Green and Alerstam [16]) for the comparison between flight directions in winds from the left and right (see text and Figure 3). When the magnitude of drift (Btrack) equals 1, there is full drift, and when it is 0, there is full compensation. Intermediate values indicate partial drift. Similarly, when the magnitude of compensation (Bheading) equals −1, there is full compensation, and when it is 0, there is full drift. Intermediate values indicate partial compensation. Levels of significance for tests of difference between average directions in winds from the left and right: *: p < 0.05, **: p < 0.01, ***: p < 0.001.
SpeciesSeasonMagnitude of Drift
Btrack		Magnitude of Compensation
Bheading		Recorded Behaviour
Cory’s shearwaterSpring0.7 **−0.3, p > 0.25Partial drift
Autumn−0.1, p > 0.5−1.1 **Full compensation
Balearic shearwaterSpring−0.1, p > 0.5−1.1 *Full compensation
Autumn−0.1, p > 0.5−1.1 **Full compensation
GannetSpring0.2, p > 0.25−0.8 *Full compensation
Autumn−0.1, p > 0.5−1.0 **Full compensation
AuksSpring−0.2, p >0.05−1.2 ***Full compensation
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Muñoz Arroyo, G.; Mateos-Rodríguez, M. Do Seabirds Control Wind Drift during Their Migration across the Strait of Gibraltar? A Study Using Remote Tracking by Radar. Remote Sens. 2022, 14, 2792. https://doi.org/10.3390/rs14122792

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Muñoz Arroyo G, Mateos-Rodríguez M. Do Seabirds Control Wind Drift during Their Migration across the Strait of Gibraltar? A Study Using Remote Tracking by Radar. Remote Sensing. 2022; 14(12):2792. https://doi.org/10.3390/rs14122792

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Muñoz Arroyo, Gonzalo, and María Mateos-Rodríguez. 2022. "Do Seabirds Control Wind Drift during Their Migration across the Strait of Gibraltar? A Study Using Remote Tracking by Radar" Remote Sensing 14, no. 12: 2792. https://doi.org/10.3390/rs14122792

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