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Article

Migratory Movements and Home Ranges of Geographically Distinct Wintering Populations of a Soaring Bird

by
Ryo Ogawa
1,*,
J. Brian Davis
1,
D. Tommy King
2,
L. Wes Burger
1,
Bronson K. Strickland
1,
Marsha A. Sovada
3,
Guiming Wang
1 and
Fred L. Cunningham
2
1
Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, Mississippi State, MS 39762, USA
2
U.S. Department of Agriculture, Wildlife Services, National Wildlife Research Center, Mississippi Field Station, Mississippi State University, Mississippi State, MS 39762, USA
3
U.S. Geological Survey, Northern Prairie Wildlife Research Center, 8711 37th Street Southeast, Jamestown, ND 58401, USA
*
Author to whom correspondence should be addressed.
Diversity 2022, 14(12), 1109; https://doi.org/10.3390/d14121109
Submission received: 7 November 2022 / Revised: 30 November 2022 / Accepted: 1 December 2022 / Published: 13 December 2022
(This article belongs to the Section Biodiversity Loss & Dynamics)
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Abstract

:
Migratory soaring birds exhibit spatiotemporal variation in their circannual movements. Nevertheless, it remains uncertain how different winter environments affect the circannual movement patterns of migratory soaring birds. Here, we investigated annual movement strategies of American white pelicans Pelecanus erythrorhynchos (hereafter, pelican) from two geographically distinct wintering grounds in the Southern and Northern Gulf of Mexico (GOM). We hypothesized that hourly movement distance and home range size of a soaring bird would differ between different geographic regions because of different thermals and wind conditions and resource availability. We calculated average and maximum hourly movement distances and seasonal home ranges of GPS-tracking pelicans. We then evaluated the effects of hour of the day, seasons, two wintering regions in the Southern and Northern GOM, human footprint index, and relative pelican abundance from Christmas Bird Count data on pelican hourly movement distances and seasonal home ranges using linear mixed models and generalized linear mixed models. American white pelicans moved at greatest hourly distance near 1200 h at breeding grounds and during spring and autumn migrations. Both wintering populations in the Northern and Southern GOM exhibited similar hourly movement distances and seasonal home ranges at the shared breeding grounds and during spring and autumn migrations. However, pelicans wintering in the Southern GOM showed shorter hourly movement distances and smaller seasonal home ranges than those in the Northern GOM. Hourly movement distances and home ranges of pelicans increased with increasing human footprint index. Winter hourly movements and home ranges of pelicans differed between the Northern and Southern GOM; however, the winter difference in pelican movements did not carry over to the shared breeding grounds during summers. Therefore, exogenous factors may be the primary drivers to shape the flying patterns of migratory soaring birds.

1. Introduction

Migration is the seasonal movement of animals between their breeding and non-breeding grounds and allows animals to exploit resources seasonally available in different regions during a year [1]. Seasonal migration of birds may span vast distances from hundreds to thousands of kilometers, a phenomenon studied for nearly two centuries [2]. Flying patterns of avian migrants (e.g., circadian variation in hourly distance and flying modes) and movement strategies (e.g., spatiotemporal variation in the duration and frequency of flying, foraging, and stopover) are fundamental behavioral mechanisms underlying long-distance migration [3]. Movement speeds and distances (e.g., short-, medium-, long-distance migrant) are just two examples of the diversity of migration strategies used by birds [3,4,5].
Birds can alter their flying patterns in response to circadian and seasonal variation in weather or climatic conditions [6,7,8]. Migratory birds can vary their movement speeds concordant with variable climatic or thermal conditions between different geographic regions and seasons to reduce flight energy costs [8,9]. Flight is the most physically challenging and energetically expensive avian activity (per unit time), particularly for large-sized migrants over long distances [10]. The energy costs of soaring and gliding are estimated to be <50% of flapping in Himalayan (Gyps himalayensis) and Eurasian (G. fulvus) Griffons [11]. Compared to flapping flight, soaring flight is influenced more by thermals, winds, and topography [6,12]. Thus, we reason that sub-populations of soaring birds wintering in different non-breeding grounds may exhibit different movement speeds if wind and thermal conditions vary inter-regionally. However, few studies have investigated movement patterns and strategies of migratory birds throughout the entire annual cycle, including migration phases [4,5].
Several other factors beyond winds and thermals can affect soaring bird movements. Availability and spatial distributions of food resources may influence animal movements, where, for example, increases in ecosystem productivity would reduce within-season bird movement speed and home ranges [13,14]. Additionally, increases in animal population size may result in “crowding” effects on individuals, reducing movement distance on wintering grounds [15]. Central-place foragers may deplete food resources in the habitat near their colonies as population size increases (“Ashmole Halo”) [16]. Intra-specific competition and subsequent food shortage would increase the home range size of central-place foraging waterbirds [17]. Anthropogenic disturbances also can affect bird and mammal movements [18,19]. Relative to disturbance, the human footprints index quantifies the degree of human disturbance to natural systems by considering a composite score of man-made environments (e.g., urban development), human population density, electric infrastructure, croplands, pasturelands, roads, railways, and navigable waterways [20]. The human footprint index correlated inversely with movements of mammals [18] and can also affect the spatial distribution of birds [21]. Cabrera-Cruz et al. (2018) studied how light pollutions influence migration passages of nocturnally migrating birds [22], but few studies have yet related individual migratory bird movement to human footprint index.
American White Pelicans (Pelecanus erythrorhynchos, hereafter pelicans) are among the largest flying birds of North America [23]. The average body mass of pelicans ranges from 4.54 kg to 7.72 kg [23], and soaring is their primary flying mode given their size [24]. The allometric scaling exponent of required energy for flapping flight is approximately double that of available energy, limiting the flapping flight capacity of large-sized birds [25]. Like other large-sized birds, pelicans have relatively long wingspan and small wing areas, making them suitable for soaring and gliding [25,26].
Most pelicans that breed in the Northern Great Plains east of the Continental Divide, United States, winter in the Northern or Southern Gulf of Mexico (GOM) [27]. The Northern and Southern GOMs differ in climate, ecosystem, landscape, and anthropogenic disturbance [28,29]. Relative abundance of pelicans in the Southern GOM increased rapidly during the years of our study and on average was twice as much than that of the Northern GOM (Supplementary Material Figure S1). King et al. investigated the migration phenology of pelicans that wintered in the Northern GOM [30], and Illan et al. studied the effects of winds and thermals on the spring and autumn migration hourly distance of the same migratory population of pelicans [31]. However, uncertainty remains whether movement patterns vary between the Northern and Southern GOM wintering individuals of pelicans. Few empirical studies have assessed geographic variation in movement patterns and strategies of the same migratory species, and no studies to our knowledge have investigated the movement patterns and migration strategies of pelicans during the entire annual cycle.
Herein, our primary objective was to study spatiotemporal variation in movement patterns of two geographically distinct wintering individuals of pelicans, and we had three primary hypotheses. First, we hypothesized that pelicans in the Southern GOM, a region of greater ecosystem productivity, greater pelican relative abundance, and lower human disturbance, would have shorter hourly movement distances and smaller seasonal home ranges than birds wintering in the Northern GOM. Second, we hypothesized that pelicans wintering in the Northern and Southern GOMs would differ in hourly movement distances and seasonal home ranges but would have similar hourly movement distances at the shared breeding grounds. We also predicted that pelicans would not differ in the maximum hourly movement distance between summer and winter seasons and regions because the maximum distance indicates the movement capability of the species in optimal conditions. Third, we hypothesized that migratory pelicans wintering farther south from the breeding grounds would fly faster than those nearer breeding grounds during spring migration.

2. Methods

2.1. Description of Study Regions

American White Pelicans of the Central and Mississippi Flyway winter either in the Southern or Northern GOM. The boundaries of the Northern and Southern GOMs were delineated based on the marine ecoregions in North America [28,29] (see the horizontal line to delineate the Northern and Southern GOMs; Figure S1). The Northern GOM spans from Gullivan Bay on the west coast of Florida through Alabama, Mississippi, Louisiana, and Texas, US to Tamaulipas, Mexico. The Southern GOM extends from Veracruz through Tabasco and Campeche to Yucatan, Mexico [28,29]. The Northern and Southern GOMs differ in sea surface temperatures in winter. Winter ambient air temperatures in the Northern GOM range from 14 to 24 °C, while those in the Southern GOM range from 24 to 25 °C [29]. The Northern GOM has tidal estuaries, fresh and salt marsh, and river inlets, which create wetland complexes that serve as an important habitat and provide food resources for migratory waterbirds [29,32]. The Southern GOM contains coastal lagoons and mangroves, river deltas, and emergent freshwater marshes, comprising the habitat of wintering migratory birds [29,32]. The Southern GOM ecosystems are more productive than the Northern GOM ecosystems owing to more precipitation, higher temperature, and mangrove ecosystems [33].

2.2. Capture Sites and Capture Methods

We captured pelicans on both breeding and non-breeding grounds with rocket nets and modified foot-hold traps [34,35]. On the breeding grounds in 2005 and 2006, we captured birds at three major colonies, Bitter Lake, South Dakota (45°14′ N, 97°20′ W), Chase Lake, North Dakota (47°01′ N, 99°27′ W), and Medicine Lake, Montana (48°30′ N, 104°30′ W) for capture site details and information on sampled pelicans [36]; Figure S2). On the non-breeding grounds of Alabama, Arkansas, Louisiana, and Mississippi from 2002 to 2010, we captured pelicans near aquaculture facilities [35] (Figure S2). We used culmen length to sex the captured pelicans [37] and aged birds as immature (≤3 years old) or mature based on plumage and eye and skin color characteristics (D. T. King, unpublished data). We attached 70 g backpack solar-powered Global Positioning System (GPS) transmitters (PTT-100, Microwave Telemetry, Inc., Columbia, MD, USA) to captured pelicans [38]. GPS transmitters were programmed to record one location per hour for a 24 h duty cycle or from 600 h to 1900 h.

2.3. GPS Location, Christmas Bird Count, and Human Footprint Data Acquisition and Processing

We did not have data on the reproductive condition or breeding status of tracked pelicans. Therefore, instead of using the terms “breeding” and “non-breeding seasons,” we divided all GPS locations of pelicans into four different biological seasons of a year: on the breeding grounds (hereafter, summer), autumn migration, on the non-breeding grounds (hereafter, winter), and spring migration in this study. The terms “summer” and “winter” referred to pelican annual biological seasons. We used net squared displacement to determine the start and end dates of each season for each tracked pelican using the “as.ltraj” function in R package “adehabitatLT” [39,40]. Net squared displacement is a squared geographic distance between the first location and each subsequent location of a tracked animal [39]. Net squared displacement remains relatively constant on the breeding grounds during summer and on the non-breeding grounds during winter but varies during spring and autumn migrations [30]. For sedentary pelicans that remained at the non-breeding grounds year-round, we set their wintering seasons from median autumn arrival date at those non-breeding grounds to median spring departure date of pelican migrants. Although we did not consider the behaviors of sedentary pelicans during summer seasons and migration periods in our analyses, we included sedentary pelicans during winter seasons in the analyses, assuming that breeding and migratory activities of pelicans would not influence their behaviors in the subsequent winter seasons.
To examine the effects of pelican relative abundance on their hourly movement distance and home range, we obtained Audubon Christmas Bird Count data from the National Audubon Society to calculate pelican relative abundance within pelican wintering grounds around GOM [41]. We used count per party hour as a relative abundance index of pelicans. The Christmas Bird Count is a volunteer-based survey, during which volunteers count birds across North America from December to January each year [41]. We used Christmas Bird Count data only from survey sites on the wintering grounds in the Northern and Southern GOMs from 2002 to 2012 (Figure S1). To account for variation in survey effort among sites and years, we built generalized additive mixed models with Poisson distributions and log link functions to predict pelican counts at each survey location using “gamm4” function in R package “gamm4” [42]. To account for survey efforts and spatial autocorrelations between survey sites, we included log-transformed survey effort hours as an offset and a smoothing term of survey year and x- and y-coordinates of survey locations [43]. We then used the predicted annual relative abundance index of pelicans within pelican wintering grounds around GOM in the analysis of hourly movement distances and seasonal home ranges.
To quantify anthropogenic disturbances in the two wintering regions, we obtained the human footprint index raster file from Socioeconomic Data and Applications Center [20]. Human footprint index uses built environments, human population density, electric infrastructure, crop lands, pasture lands, roads, railways, and navigable waterways to score the human pressure levels in the 1 km spatial resolution [20]. We used human footprint index calculated in 2009 for the birds tracked from 2002 to 2012 [44].
We calculated hourly movement distances (km/h) during each season (i.e., winter, spring migration, summer, and autumn migration) and seasonal home ranges (km2) for each tracked pelican each year. We calculated hourly movement distances between successive hourly locations of individual pelicans and then calculated mean hourly movement distance for each hour of a day by season for each tracked pelican. Thus, calculations of hourly movement distance only used two locations 1 h apart. To estimate unbiased geographic distances, we calculated the great circle distances using “distVincentyEllipsoid” function in R package “geosphere” [45]. We also determined maximum hourly movement distances for each hour of a day by season for each tracked pelican. Maximum hourly movement distance indicates movement capacity, suggesting how fast birds can fly in optimal conditions. Therefore, our statistical sample unit of hourly mean and maximum distances was an individual bird in a season.
We estimated the 95% seasonal home ranges of pelicans for summer, winter, spring migration, and autumn migration seasons, respectively, using dynamic Brownian bridge movement models (DBBMM) with the “Brownian.bridge.dyn” function in R package “move” [46]. The DBBMMs estimate animal home ranges accounting for heterogeneous changes in animal behavior [47]. The DBBMM is appropriate for estimating pelican home ranges because pelicans are highly mobile, and their movement lacks central tendency during migration. Although the spacing behavior and the geometric shape of habitats intensively used of migration phases may be different from those during the breeding and non-breeding seasons, we used the term home ranges for migration phases for consistency. To parameterize the DBBMM, we set location error, window size, margin, and time step of the DBBMM to 30 m, 23 h (approximately one day), 11 h (approximately half time of window size), and 15 steps per hour, respectively. We then extracted and averaged human footprint indices within the boundary of each seasonal home ranges to examine the effects of anthropogenic disturbance on the hourly movement distances and seasonal home ranges of each pelican in each season.

3. Statistical Analyses

3.1. Daily Maximum and Average Hourly Movement Distance or Speed

We used generalized linear mixed models (GLMMs) to assess the effects of season, wintering group (i.e., the Northern or Southern GOM), population relative abundance, year, and human disturbance on the seasonal average hourly movement distances of pelicans (i.e., 24 hourly mean distances of each season for each bird). We built GLMMs with the Gamma distribution and log link function for movement distances [48]. We included season, wintering group, winter relative abundance index, year, and human footprint index as fixed effects and animal identity as a random effect. Year and relative abundance index were correlated with each other (Pearson’s correlation r = 0.88; Figure S3); therefore, we built two sets of models to include only one of the two covariates in each set of models, respectively (Table 1, Table 2 and Table 3). To account for circadian variations in hourly movement distances of pelicans, we incorporated Fourier transformations of time (i.e., hours) using the sine and cosine functions of time in the frequencies of 1/24 and 1/12 cycles per hour into our models. The two frequencies corresponded to the daily (i.e., a 24-h cycle) and daytime (a 12-h cycle) rhythms, respectively. With the circadian movements being accounted for, we can test whether hourly movement distance differed between regions using the marginal means. To investigate region-specific seasonal variations in the hourly movement distances of pelicans between the Northern and Southern GOMs, we included interactions among circadian hour, wintering group, and season in GLMMs.
We used Akaike information criterion (AIC) for model selection with the most parsimonious model having the lowest AIC among a set of candidate models [49]. We conducted model selection in a backward manner, starting with a full model including all fixed effects and their interactions. We considered models with ΔAIC of <2.0 as competing models [49].
If there was an interaction between wintering group and season in the selected models, we estimated the marginal means of movement metrics and their 95% confidence intervals (CIs) for each wintering group. If the 95% CIs of two marginal means did not overlap, we concluded the two means differed. If the 95% CI of a regression coefficient did not include zero, we concluded that the coefficient was significantly different from zero.
We also examined whether the departure and arrival dates of spring migration would differ between the two wintering groups of pelicans in the Northern and Southern GOMs using a t-test.

3.2. Seasonal Home Range and Used Area on the Migratory Flyway

We built linear mixed models (LMMs) to evaluate the effects of season, wintering group, relative population abundance index, year, and human footprint index on seasonal home ranges and used areas on the migratory flyway with bird identity as a random effect. We log transformed the home ranges and used areas for the normality assumption. We also included interactions between annual population abundance index, wintering ground, and season as well as between season and human footprint index. We used the same model approaches to the model selection and pairwise comparisons of LMMs as those to the aforementioned GLMMs.
We used the R package “glmmTMB” in the R 3.6.2 environment for LMMs and GLMMs and R package “MuMIn” to calculate ΔAIC [50,51]. The marginal means and their 95%CIs were calculated using the R package “emmeans” [52].

4. Results

We analyzed hourly location data of 72 GPS-tracked pelicans from 2002 to 2012. Twenty-four birds were captured on the breeding grounds at Chase Lake, Medicine Lake, and Bitter Lake, while the remaining 48 birds were captured on the non-breeding grounds (Figure S2). The effects of years on hourly movement distances and seasonal home ranges of pelicans were similar to those of pelican relative abundance (Figure S3, and Tables S1 and S2). Subsequently, we only reported the effects of pelican relative abundance on movement distances and home ranges. Neither departure nor arrival dates of spring migration differed between the wintering Northern and Southern GOM groups (departure: t = 0.92, df = 46.02, p = 0.36; arrival: t = 0.90, df = 45.97, p = 0.38).

4.1. Seasonal Hourly Movement Distance

The best GLMM of average hourly movement distance included human footprint indices (hfp) and interactions between circadian hours, seasons, and wintering groups plus interactions among seasons, wintering groups, and pelican relative abundance indices. The second-best model included a season-hfp interaction and had ΔAIC of 1.08 (Table 1). Based on the parsimony principle, we chose the simpler (i.e., the best model) between the two competing models as the final model to represent average hourly movement distance.
American White Pelicans exhibited a 12 h cycle of movement rhythm at the breeding grounds and during spring and autumn migrations (Figure 1). The marginal means of winter average hourly movement distance were greater in the Northern than in the Southern GOM (Northern GOM: distance = 1.62 [km], 95% CI [1.43–1.84]; Southern GOM: distance = 0.81 [km], 95% CI [0.63–1.05]). However, marginal mean hourly movement distance did not differ between Northern and Southern GOMs during summer (Northern GOM: distance = 1.66 [km], 95% CI [1.45–1.90]; Southern GOM: distance = 1.25 [km], 95% CI [0.99–1.57]), spring migration (Northern GOM: distance = 3.15 [km], 95% CI [2.74–3.63]; Southern GOM: distance = 3.06 [km], 95% CI [2.36–3.98]), nor autumn migration (Northern GOM: distance = 2.66 [km], 95% CI [2.31–3.09]; Southern GOM: distance = 2.60 [km], 95% CI [2.06–3.26]) (Figure 1). Marginal mean hourly movement distances were greater during spring and autumn migration than during summer and winter; however, marginal mean hourly movement distances did not differ between spring and autumn migration (Figure 1).
Average hourly movement distances of pelicans were positively related to human footprint indices (β = 0.06, 95% CI [0.03–0.09]). Average hourly movement distances of the Northern GOM wintering group were inversely related to winter pelican relative abundance indices during summer and autumn migration (summer season: β = −0.05, 95% CI [−0.07–−0.03]; autumn migration: β = −0.04, 95% CI [−0.06–−0.01]; Figure 2a,d), but neither in the winter nor during spring migration (winter season: β = −0.001, 95% CI [−0.02–0.02]; spring migration: β = −0.001, 95% CI [−0.02–0.02]; Figure 2b,c). Average hourly movement distances of the Southern GOM wintering group were inversely related to pelican relative abundance in the winter (winter season: β = −0.11, 95% CI [−0.17–−0.05]; Figure 2b), but neither in the summer nor spring or autumn migration (summer season: β = −0.03, 95% CI [−0.07–0.01]; spring migration: β = −0.01, 95% CI [−0.07–0.09]; autumn migration: β = 0.03, 95% CI [−0.02–0.07]; Figure 2a,c,d).

4.2. Seasonal Maximum Hourly Movement Distance

Among the top three models ranked by AIC, we chose the second-best model (ΔAIC = 0.11), the simplest model, to represent maximum hourly movement distance (Table 2). Maximum hourly movement distances also had a 12 h cycle of rhythm with a peak hourly distance around 1300 h at the breeding grounds and during spring and autumn migrations (Figure 3). The 95% CIs of maximum hourly movement distance overlapped during the summers, winters, and spring and autumn migration (Figure 3). Maximum hourly movement distances of the Northern GOM wintering group were inversely related to winter pelican relative abundance indices during the summer (β = −0.06, 95% CI [−0.08–−0.04]), the winter (β = −0.03, 95% CI [−0.05–−0.01]), and spring (β = −0.04, 95% CI [−0.07–−0.02]) and autumn migration (β = −0.03, 95% CI [−0.06–−0.01]) (Figure 4). Likewise, maximum hourly movement distances of the Southern GOM wintering groups were inversely related to winter pelican relative abundance during the summer (β = −0.05, 95% CI [−0.08–−0.01]), the winter (β = −0.14, 95% CI [−0.20–−0.09]), autumn migration (β = −0.07, 95% CI [−0.10–−0.03]), but not during spring migration (β = −0.06, 95% CI [−0.14–0.02]) (Figure 4).

4.3. Seasonal Home Range and Used Area on the Migratory Flyway

American White Pelicans wintering in both the Northern and Southern GOMs shared the breeding grounds in the Northern Great Plains (Figure 5a). American White Pelicans wintering in the Southern GOM had a single relatively linear flying corridor from south Texas to the breeding grounds during spring migration (Figure 5c). The spring migration routes of the Northern GOM wintering group forked between the Mississippi River and Arkansas River, covering larger areas than those of the Southern GOM group (Figure 5c).
The best LMM of seasonal home ranges and used areas on the flyway included human footprint index, interaction between pelican relative abundance and wintering grounds, and interaction between seasons and wintering grounds (Table 3). The second-best model was a competing model (ΔAIC = 1.17), including pelican relative abundance, human footprint index, and interaction between seasons and wintering grounds (Table 3). We chose the simpler second-best model to represent seasonal home range and used area. Seasonal home ranges and used areas of pelicans were positively related to human footprint indices (β = 0.50, 95% CI [0.32–0.68]), but were inversely related to pelican relative abundance (β = −0.33, 95% CI [−0.56–−0.09]). The marginal mean of winter home ranges was larger in the Northern GOM (log-home-range [km2] = 8.72, 95% CI [8.35–9.10]) than in the Southern GOM (log-home-range [km2] = 6.39, 95% CI [5.68–7.11]) during winter seasons (Figure 5b).

5. Discussion

Avian migrants often exhibit spatiotemporal variation in the mode, speed, and duration of flights in response to changes in climate, wind, and food availability [9,54,55,56]. Migratory birds generally fly faster in spring migration than in autumn migration for timely arrival at the breeding ground [57]; but also see the opposite results in [56,58]. Long-distance avian migrants change stopover duration to minimize overall migration time [56]. Large-sized soaring birds primarily use external sources of energy for migration flights [59]. Our results supported the hypothesis that hourly movement distance and home ranges of soaring pelicans would be different at different non-breeding grounds but would be similar when living at the same breeding grounds, indicating the primary effects of exogenous factors. However, our findings did not support the hypothesis that pelicans departing from the Southern GOM would fly faster than those departing from the Northern GOM despite comparable departure and arrival dates of spring migration between the two groups. Because the size of migratory used area between two wintering groups did not differ during spring and autumn migrations, the total migration distances may not differ in the two wintering grounds between the Northern and Southern GOMs. Furthermore, we also found evidence that pelicans reduced hourly average and maximum hourly flying distances with increasing pelican relative abundance within their wintering region (for possible different ecosystem productivity and human disturbances) being accounted for. Individual pelicans may gather in resource rich areas that require less movement to meet daily energy needs through more efficient foraging [13,60]. Increased anthropogenic disturbances also increased hourly mean flying distance and seasonal home ranges of pelicans.
Temperatures, winds, thermals, and individual differences affect bird flying performance [7,31,61,62]. Illan et al. found that tailwind speed and uplift intensity affected hourly flying distance of pelicans during spring and autumn migrations [31]. In our study, pelicans in the Northern GOM had higher hourly flying speeds and larger home ranges than in the Southern GOM during winter seasons, after accounting for circadian rhythm, anthropogenic disturbances, pelican relative abundance, and individual random effects. As most tracked pelicans used in this study had at least one migration trip with observations at both breeding and non-breeding grounds, the difference in hourly flying speed between the two wintering groups may be attributable to unmeasured differences in climatic conditions and food availability between the two regions. Furthermore, pelicans that were subject to similar climate and wind conditions on the shared breeding grounds and migration corridors did not differ in flying speed. Therefore, exogenous environmental factors such as food availability, thermals, air uplift intensity, and wind conditions (e.g., speed and direction) may dictate the hourly flying distance of pelicans [63]. However, our study did not directly quantify relationships between hourly movement distance or distance and climatic or atmospheric conditions. Future studies need to model the relationships between the movement patterns and exogenous variables to elucidate the mechanisms underlying the observed patterns of pelican seasonal movements.
Avian migrants may have higher total flying speed during spring migration than during autumn migration for timely arrival at the breeding grounds [56]. As expected, we found that pelicans flew faster during spring and autumn migration than during winter and summer. However, hourly flying distance did not differ between spring and autumn migration. The similar hourly flying distance may be because pelicans mainly use soaring flight to complete spring and autumn migration without much flapping flight [24]. High reliance of soaring flight on thermals and wind conditions may result in comparable hourly flying distance of pelicans between spring and autumn migration. Although pelicans wintering in the Southern GOM did not fly faster than those in the Northern GOM, the birds of different wintering individuals may differ in the number of stopover sites and stopover duration, which can be used to adjust total flying duration [56], given the similar spring departure and arrival timing between the two pelican groups. Alternatively, our results of the same used areas during migration between the Southern and Northern GOM groups may demonstrate that the overall migratory distances are the same for the two wintering grounds. Our GPS data had gaps along migratory tracks, preventing us from measuring stopover duration during spring migration. Future studies need to use fine-resolution GPS location data to better understand pelican migration strategies.
Hourly flying distance and home ranges of pelicans increased with increasing human footprint index. Anthropogenic disturbances may affect bird movements in at least two ways. First, anthropogenic disturbances may fragment avian habitat (including inland freshwater wetlands—pelican foraging habitat), breaking habitat up into small patches and thus increasing distance between habitat or food patches. The resource dispersion hypothesis predicts that movement distances and home ranges increase with increasing habitat or resource fragmentation [64]. For instance, Eastern Wild Turkeys (Meleagris gallopavo silvestris) move longer distances on more fragmented habitat [65]. Second, birds may fly a longer time and more distance with more intensified human disturbances. Lilleyman et al. (2016) found that human disturbances at the roost sites increased the flight times and distance of shorebirds (Calidris spp. and Charadrius spp.) during winter [19]. Increases in movements induced by human disturbances reduce the energy reserve during winter, likely bearing demographic consequences in migratory birds [66]. Increases in human disturbances during the non-breeding period are likely to be a driver of overall declines of the eastern populations of Canada Warblers (Cardellina canadensis) [66]. However, human disturbances increased the movement distance of roosting Eurasian Oystercatchers (Haematopus ostralegus) but marginally affected their daily energy budget [67]. Future studies are needed to investigate the effects of anthropogenic disturbances on the movement, daily energy budget, and demography of migratory birds at the non-breeding grounds using biologging and demographic modeling [68].
Inverse relationships between population abundance and home range size are well established in mammals [15]. Reduced home range size and daily movement distance have been ascribed to increased aggression toward conspecifics. Intensified social fence and territoriality with increasing population density have been invoked as a behavioral mechanism of density dependence and population regulation of mammalian populations. Previous studies have commonly used the availability or amount of resources to explain home range or territory sizes of birds [69,70]. Few studies have used population density to explain bird home range sizes. Home range size of male Swainson’s Warblers (Limnothlypis swainsonii) is inversely related to the number of competing male warblers [71]. In addition to intensified competition for resources with increased densities, social interactions such as increased aggression may affect bird movement and spacing behavior. Papageorgiou and Farine have found that social group size reduced home ranges of Vulturine Guineafowl (Acryllium vulturinum) when group size exceeded a threshold [72]. We found that home range size and hourly movement distance decreased with increasing pelican relative abundance. This study used the Christmas Bird Count index as relative abundance index of pelicans given that estimates of pelican winter abundance and densities with rigorous survey methods were not available for a large area such as the Northern and Southern GOM. However, we caution that the Christmas Bird Count index may not accurately measure temporal variation in pelican population abundance.

6. Conclusions

American White Pelicans exhibited seasonal variation in hourly flying distance. Furthermore, pelican hourly flying distance differed between the Northern and Southern GOM, demonstrating regional difference, during winter. However, winter regional differences in movement and spacing did not carry over to the breeding grounds during summer. Anthropogenic disturbances increased hourly flying distance and home range size on the non-breeding grounds during winter. Exogenous factors may be the primary factors determining the movement pattern and spacing behavior of soaring birds.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d14121109/s1, Figure S1: Estimated annual pelican population counts per survey site by Christmas Bird Counts (CBC) from 1974 to 2017 in the Northern and Southern Gulf of Mexico (GOM) (left panels). The calculation of the estimated CBC was conducted separately using generalized additive models (See the methods of the text; 4243 vs. 126 observations at Northern and Southern GOMs, respectively). Right panel indicates the location of CBC survey. A horizontal line in the right panel separates the survey sites between Northern and Southern GOMs. Figure S2: Capture sites of American White Pelicans at breeding and non-breeding grounds. Figure S3: Relationships between year and estimated Christmas bird counts per survey site. Figure S4: Hourly movement distances of American White Pelicans from 2002 to 2012. Blue and red colors represent wintering populations at the Northern and Southern Gulf of Mexico, respectively. Panels show (a) breeding, (b) wintering, (c) spring migration, and (d) autumn migration. Polygons represent 95% confidence intervals of the lines. Figure S5: Maximum hourly movement distances of American White Pelicans from 2002 to 2012. Blue and red colors represent wintering populations at the Northern and Southern Gulf of Mexico, respectively. Panels show (a) breeding, (b) wintering, (c) spring migration, and (d) autumn migration. Polygons represent 95% confidence intervals of the lines. Table S1: Generalized linear mixed models of average hourly movement distances of American white pelicans. Table S2: Generalized linear mixed models of maximum hourly movement distances of American white pelicans. Table S3: Linear mixed models of seasonal home ranges and used areas on the migratory flyway of American white pelicans.

Author Contributions

Conceptualization, R.O., G.W., and F.L.C.; methodology, R.O. and G.W.; formal analysis, R.O.; resources, D.T.K. and M.A.S.; data curation, R.O.; writing—original draft preparation, R.O. and G.W.; writing—review and editing, R.O., J.B.D., D.T.K., L.W.B., B.K.S., M.A.S., G.W. and F.L.C.; visualization, R.O.; supervision, J.B.D., L.W.B., B.K.S., G.W. and F.L.C.; project administration, F.L.C.; funding acquisition, G.W. and F.L.C. All authors have read and agreed to the published version of the manuscript.

Funding

United States Department of Agriculture, Animal and Plant Health Inspection National Wildlife Research Center, Cooperative Service Agreement: 19-7428-1424 (CA).

Institutional Review Board Statement

All experimental protocols of animal capture and handling were approved by the United States Department of Agriculture (USDA), National Wildlife Research Center, Institutional Animal Care and Use Committee (IACUC Protocol QA-1018) for pelicans captured in the Northern GOM and by Northern Prairie Wildlife Research Center’s Animal Care and Use Committee (Project Number: NN00.0LLX3) for pelicans captured in the Northern Great Plains.

Data Availability Statement

Datasets are accessible from the corresponding author on reasonable request.

Acknowledgments

This publication is a contribution of the Forest and Wildlife Research Center, Mississippi State University. Ryo Ogawa and Guiming Wang were also supported by the Department of Wildlife, Fisheries and Aquaculture at Mississippi State University Forest and Resource Center. J. Brian Davis was supported by the James C. Kennedy Chair in Waterfowl & Wetlands Conservation. D. Tommy King and Fred L. Cunningham were supported by the USDA WS/National Wildlife Research Center. Marsha A. Sovada was supported by the USGS Northern Prairie Wildlife Research Center. The findings and conclusions in this publication are those of the author(s) and should not be construed to represent any official USDA or U.S. Government determination or policy.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Average hourly movement distances of American White Pelicans with circadian hours. Blue and red colors represent wintering groups at Northern and Southern Gulf of Mexico, respectively. Panels represent (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Bars show observed average hourly movement distances. Lines indicate the estimated average hourly movement distances based on the best model. Polygons represent 95% confidence intervals of the average hourly movement distances.
Figure 1. Average hourly movement distances of American White Pelicans with circadian hours. Blue and red colors represent wintering groups at Northern and Southern Gulf of Mexico, respectively. Panels represent (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Bars show observed average hourly movement distances. Lines indicate the estimated average hourly movement distances based on the best model. Polygons represent 95% confidence intervals of the average hourly movement distances.
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Figure 2. Effects of seasons and relative population abundance on average hourly movement distances of American White Pelicans. Panels show (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Blue and red colors represent wintering groups at Northern and Southern Gulf of Mexico, respectively. Polygons represent 95% confidence intervals of the average hourly movement distances.
Figure 2. Effects of seasons and relative population abundance on average hourly movement distances of American White Pelicans. Panels show (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Blue and red colors represent wintering groups at Northern and Southern Gulf of Mexico, respectively. Polygons represent 95% confidence intervals of the average hourly movement distances.
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Figure 3. Maximum Hourly movement distances of American White Pelicans with circadian hours. Blue and red colors represent wintering groups at Northern and Southern Gulf of Mexico, respectively. Panels represent (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Bars show observed maximum hourly movement distances. Lines indicate the estimated maximum hourly movement distances based on the best model. Polygons represent 95% confidence intervals of the maximum hourly movement distances.
Figure 3. Maximum Hourly movement distances of American White Pelicans with circadian hours. Blue and red colors represent wintering groups at Northern and Southern Gulf of Mexico, respectively. Panels represent (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Bars show observed maximum hourly movement distances. Lines indicate the estimated maximum hourly movement distances based on the best model. Polygons represent 95% confidence intervals of the maximum hourly movement distances.
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Figure 4. Effects of seasons and relative population abundance on maximum hourly movement distances of American White Pelicans. Panels show (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Blue and red colors represent wintering groups at Northern and Southern Gulf of Mexico, respectively. Polygons represent 95% confidence intervals of the maximum hourly movement distances.
Figure 4. Effects of seasons and relative population abundance on maximum hourly movement distances of American White Pelicans. Panels show (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Blue and red colors represent wintering groups at Northern and Southern Gulf of Mexico, respectively. Polygons represent 95% confidence intervals of the maximum hourly movement distances.
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Figure 5. Seasonal home ranges and used areas on the migratory flyway of American White Pelicans estimated by dynamic Brownian bridge movement models. Panels show (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Blue and red polygons represent the home ranges and used areas of pelicans wintering in the Northern and Southern Gulf of Mexico, respectively. The background maps in lower subpanels were produced by ArcGIS Pro [53]. Upper subpanels show the estimates and 95% confidence intervals of log-transformed home ranges and used areas at each wintering group.
Figure 5. Seasonal home ranges and used areas on the migratory flyway of American White Pelicans estimated by dynamic Brownian bridge movement models. Panels show (a) summer, (b) winter, (c) spring migration, and (d) autumn migration. Blue and red polygons represent the home ranges and used areas of pelicans wintering in the Northern and Southern Gulf of Mexico, respectively. The background maps in lower subpanels were produced by ArcGIS Pro [53]. Upper subpanels show the estimates and 95% confidence intervals of log-transformed home ranges and used areas at each wintering group.
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Table
Table 1. Generalized linear mixed models of average hourly movement distances of American White Pelicans.
Table 1. Generalized linear mixed models of average hourly movement distances of American White Pelicans.
Model a,bdf c∆AIC dAIC Weights e
(sin + cos) × ssn × g + ssn × g × cbc + hfp510.000.63
(sin + cos) × ssn × g + ssn × g × cbc + ssn × hfp541.080.37
(sin + cos) × ssn × g + ssn × g × cbc5013.570.00
(sin + cos) × ssn × g + ssn × cbc + hfp4713.720.00
(sin + cos) × ssn × g + (g + ssn) × cbc + hfp4815.360.00
(sin + cos) × ssn × g + cbc + hfp4432.610.00
(sin + cos) × ssn × g + g × cbc + hfp4534.640.00
(sin + cos) × ssn × g + hfp4338.150.00
(sin + cos) × (g + ssn) + ssn × g × cbc + hfp3953.040.00
(sin + cos) × ssn + ssn × g × cbc + hfp3569.680.00
(sin + cos) × g + ssn × g × cbc + hfp27794.130.00
(sin + cos) + ssn × g × cbc + hfp23801.750.00
a Variables in models: (sin + cos): Circadian hours with Fourier transformation of sine and cosine function; ssn: Season (i.e., summer and winter seasons and spring and autumn migration); g: Wintering individual group (the Northern or Southern Gulf of Mexico); cbc: Population relative abundance index estimated by Christmas Bird Count; and hfp: Human footprint index within seasonal home ranges of pelicans. b All models with interactions include main effects. c df: Degree of freedom. d ∆AIC: Difference in Akaike information criterion between a model and the most parsimonious model. e AIC weight: Proportional weight of Akaike information criterion at each model.
Table
Table 2. Generalized linear mixed models of maximum hourly movement distances of American White Pelicans.
Table 2. Generalized linear mixed models of maximum hourly movement distances of American White Pelicans.
Model a,bdf c∆AIC dAIC Weight e
(sin + cos) × ssn × g + ssn × g × cbc + ssn × hfp540.000.37
(sin + cos) × ssn × g + ssn × g × cbc500.110.35
(sin + cos) × ssn × g + ssn × g × cbc + hfp510.660.27
(sin + cos) × ssn × g + cbc437.710.01
(sin + cos) × ssn × g + g × cbc448.160.01
(sin + cos) × ssn × g + ssn × cbc4611.890.00
(sin + cos) × ssn × g + (g + ssn) × cbc4712.450.00
(sin + cos) × (g + ssn) + ssn × g × cbc3819.460.00
(sin + cos) × ssn + ssn × g × cbc3434.220.00
(sin + cos) × ssn × g4245.190.00
(sin + cos) × g + ssn × g × cbc26322.990.00
(sin + cos) + ssn × g × cbc22330.480.00
a Variables in models: (sin + cos): Circadian hours with Fourier transformation of sine and cosine function; ssn: Season (i.e., summer and winter seasons and spring and autumn migration); g: Wintering individual group (the Northern or Southern Gulf of Mexico); cbc: Population relative abundance index estimated by Christmas Bird Count; and hfp: Human footprint index within seasonal home ranges of pelicans. b All models with interactions include main effects. c df: Degree of freedom. d ∆AIC: Difference in Akaike information criterion between a model and the most parsimonious model. e AIC weight: Proportional weight of Akaike information criterion at each model.
Table
Table 3. Linear mixed models of seasonal home ranges and used areas on the migratory flyway of American White Pelicans.
Table 3. Linear mixed models of seasonal home ranges and used areas on the migratory flyway of American White Pelicans.
Model a,bdf c∆AIC dAIC Weight e
ssn × g + g × cbc + hfp130.000.54
ssn × g + cbc + hfp121.170.30
ssn × g + g × cbc + ssn × cbc + hfp163.780.08
ssn × g + ssn × cbc + hfp155.560.03
ssn × g + hfp115.730.03
ssn × g × cbc + hfp199.400.00
ssn × g × cbc + ssn × hfp2210.780.00
ssn × g1029.510.00
ssn × g × cbc1838.490.00
ssn + g × cbc + hfp1045.580.00
g × cbc + ssn × cbc + hfp1347.410.00
ssn + g770.940.00
a Variables in models: ssn: Season (i.e., summer and winter seasons and spring and autumn migration); g: Wintering individual group (the Northern or Southern Gulf of Mexico); cbc: Population relative abundance index estimated by Christmas Bird Count; and hfp: Human footprint index within seasonal home ranges of pelicans. b All models with interactions include main effects. c df: Degree of freedom. d ∆AIC: Difference in Akaike information criterion between a model and the most parsimonious model. e AIC weight: Proportional weight of Akaike information criterion at each model.
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Ogawa, R.; Davis, J.B.; King, D.T.; Burger, L.W.; Strickland, B.K.; Sovada, M.A.; Wang, G.; Cunningham, F.L. Migratory Movements and Home Ranges of Geographically Distinct Wintering Populations of a Soaring Bird. Diversity 2022, 14, 1109. https://doi.org/10.3390/d14121109

AMA Style

Ogawa R, Davis JB, King DT, Burger LW, Strickland BK, Sovada MA, Wang G, Cunningham FL. Migratory Movements and Home Ranges of Geographically Distinct Wintering Populations of a Soaring Bird. Diversity. 2022; 14(12):1109. https://doi.org/10.3390/d14121109

Chicago/Turabian Style

Ogawa, Ryo, J. Brian Davis, D. Tommy King, L. Wes Burger, Bronson K. Strickland, Marsha A. Sovada, Guiming Wang, and Fred L. Cunningham. 2022. "Migratory Movements and Home Ranges of Geographically Distinct Wintering Populations of a Soaring Bird" Diversity 14, no. 12: 1109. https://doi.org/10.3390/d14121109

APA Style

Ogawa, R., Davis, J. B., King, D. T., Burger, L. W., Strickland, B. K., Sovada, M. A., Wang, G., & Cunningham, F. L. (2022). Migratory Movements and Home Ranges of Geographically Distinct Wintering Populations of a Soaring Bird. Diversity, 14(12), 1109. https://doi.org/10.3390/d14121109

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