Seabirds inhabiting large, multispecies colonies face intraspecific and interspecific competition for prey and this often results in foraging strategies that partition resources. Here, we identified mechanisms that facilitate partitioning of resources between 2 congeneric tropical seabirds, Great Frigatebirds (Fregata minor) and Lesser Frigatebirds (F. ariel), for which traditional research methods have documented high levels of resource overlap. Stable isotope analysis (SIA) indicated that throughout the breeding cycle, male and female Great Frigatebirds consumed prey with higher δ15N compared to male Lesser Frigatebirds. This trend was not significant when comparing δ15N values of male and female Great Frigatebirds to female Lesser Frigatebirds. During the breeding period, GPS tracking and SIA indicated considerable spatial overlap among species and sexes. This contrasted with SIA of samples that provide insight into nonbreeding resource acquisition because these indicated that male Great Frigatebirds and male Lesser Frigatebirds had lower δ13C values than females of each species, signifying greater use of offshore foraging grounds by males of both species. Together these results suggest that body size differences influence trophic position of the prey consumed. Furthermore, central-place foraging constraints, and spatially unpredictable resource distribution, limit potential for spatial differences in foraging strategies when breeding. By contrast, spatial distribution of foraging differs during the nonbreeding period as the requirement for central-place foraging is lifted.
Organisms that use shared resources cannot persist in sympatry if ecological overlap with respect to a limiting resource is too great (Gause 1934, Hutchinson 1959, Hardin 1960, Macarthur and Levins 1967). To alleviate this potential conflict, community members partition resources by adopting a diversity of ecological strategies (MacArthur 1957). With respect to food resources, morphological, physiological, and behavioral factors are influential in determining the type of prey consumed, spatial aspects of the foraging strategy, and foraging method used.
During the breeding season, seabirds are central-place foragers because they must periodically return to their colony to undertake incubation duties and to provision young. Range limits resulting from this requirement are further mediated by individual body condition and the condition of their offspring (Chaurand and Weimerskirch 1994, Weimerskirch 1998). The resulting pattern of prey use can generate relatively intense foraging close to the colony (Elliott et al. 2009). In these circumstances, prey resources in the waters surrounding large seabird colonies can become depleted due to sustained foraging activity by the seabird assemblage (Ashmole 1963, Furness and Birkhead 1984, Birt et al. 1987, Lewis et al. 2001). Resource depletion leads to conditions that induce competition.
Many polar, temperate, and tropical seabird assemblages display resource partitioning where there is competition for prey resources. A number of attributes including prey species or prey size specificities (Ashmole and Ashmole 1967, Rayner et al. 2008), foraging location (Henkel 2009, Wakefield et al. 2013), diving capacity (Linnebjerg et al. 2015), or diel patterns in foraging (Spear et al. 2007) facilitate resource partitioning among members of the seabird community. These attributes may be contrasted between different species (Weimerskirch et al. 1988) or within a single species between different populations, sexes, or age classes (González-Solís et al. 2000, Grémillet et al. 2004, Steenweg et al. 2011, Wakefield et al. 2013). Primary productivity strongly influences how these contrasts manifest (Young et al. 2010b, Kappes et al. 2011). Primary productivity is also important for structuring the distribution of seabirds when not breeding. At the cessation of breeding, adults no longer support dependent offspring and migration or dispersal away from the colony may further diminish competition for resources (Ashmole 1963). Migrating or dispersing individuals often track regions of high primary productivity with greater prey availability (González-Solís et al. 2007, Egevang et al. 2010, Jessopp et al. 2013, McKnight et al. 2013).
Tropical marine systems are one area where primary productivity is generally low and the distribution of resources is often more patchy and unpredictable than in temperate locations (Ainley and Boekelheide 1984, Weimerskirch 2007). Many tropical seabirds have evolved wing morphology conducive to efficient flight that enables them to cover large areas when searching for unpredictable prey resources (Brewer and Hertel 2007). This morphology is not suited to underwater propulsion and constrains most tropical seabirds to surface foraging (Spear et al. 2007). Surface foraging and low productivity further interact to increase levels of competition and thus drive strong selection for foraging strategies that effectively partition prey resources.
Frigatebirds (Fregata spp.) are seabirds with a pantropical distribution. They display reverse sexual dimorphism, with females ∼30% larger than males (Mott et al. 2015). At many breeding colonies 2 or more frigatebird species occur in sympatry (Diamond 1975, King 1986, James and McAllan 2014). Unlike other seabirds, the plumage and wing structure of frigatebirds renders them incapable of settling on the sea surface (Mahoney 1984, Orta 1992, Weimerskirch et al. 2004). When foraging they remain airborne and rely on the activity of subsurface predators such as tunas and dolphins to drive prey to the surface and enable prey capture (Au and Pitman 1986, Spear et al. 2007). As such, foraging opportunities are expected to be even more restricted for frigatebirds when compared with other tropical seabirds, resulting in heightened competition for prey. It is therefore counterintuitive that previous studies have indicated high levels of resource overlap between sympatric frigatebird species (Pocklington 1979, Dunlop et al. 2001), leading some to conclude that frigatebirds display the highest degree of niche overlap of any seabird species-pair (Diamond 1975).
With recent developments in tracking technologies and the application of stable isotope analysis, it is now possible to investigate patterns of seabird resource use at a level of detail previously unattainable (Bearhop et al. 2004, Cooke et al. 2004, Ropert-Coudert and Wilson 2005, Inger and Bearhop 2008). Furthermore, these techniques allow investigation of resource use patterns over extended temporal periods. These developments present opportunities to reexamine questions where traditional methods such as direct identification of dietary items and at-sea survey have been unable to resolve patterns of resource partitioning. Here, we sought to apply these techniques to determine how sympatric populations of Great Frigatebirds (Fregata minor) and Lesser Frigatebirds (F. ariel) partition available prey resources. In doing so we also sought to identify mechanisms that facilitate coexistence of these remarkably similar congeners.
Fieldwork was conducted at Ashmore Reef (12.27°S, 123.03°E), an Australian territory in the Timor Sea. Ashmore Reef is recognized by BirdLife International as an Important Bird Area (IBA) (BirdLife International 2013) and supports 16 species of breeding seabirds with more than 100,000 individuals (Clarke et al. 2011). Great Frigatebirds (65 individuals) and Lesser Frigatebirds (4,196 individuals) both breed at Ashmore Reef (Clarke et al. 2011, Clarke and Herrod 2014). Great Frigatebirds nest in small Heliotropium foertherianum shrubs, whereas Lesser Frigatebirds nest on the ground among low grassy and/or herbaceous vegetation. Breeding of both species in this basin is seasonally predictable with laying occurring mid-February through May (Clarke et al. 2011).
Bird Capture and Sampling
Adult birds were captured at their nests during incubation and early chick-rearing periods in March and April of 2014. Birds were captured at night to reduce incidences of heat stress. Individuals were sexed based on plumage characteristics (Marchant and Higgins 1990), weighed (Salter Super Samson, Springvale, Victoria, Australia) and fitted with a metal leg band supplied by the Australian Bird and Bat Banding Scheme. A global positioning system (GPS) device programmed to record a position every 5 min was attached with Tesa tape to 3 central rectrices of the tail (CatTrack 1, Catnip Technologies, Hong Kong: Great Frigatebird n = 6, Lesser Frigatebird n = 26) or by a Teflon leg-loop harness (HARIER-4L, Ecotone Telemetry, Sopot, Poland: Great Frigatebird n = 6, Lesser Frigatebird n = 9) (Mott et al. 2015). CatTrack devices were archival-type loggers sealed in waterproof heatshrink. HARIER-4L devices were capable of transmitting stored data via UHF frequencies to a base station established on the island, thus negating the need to recapture a bird to recover data. Bird-borne devices had a total mass of ∼26 g for CatTrack devices and 15 g for HARIER-4L devices. The minimum and maximum percentage of body mass for any logger deployment were 0.97% and 2.68%, respectively, for Great Frigatebirds, and 1.61% and 3.92%, respectively, for Lesser Frigatebirds. At initial capture, 5 breast feathers were plucked from each bird for later analysis and a blood sample (∼0.5 mL) was collected from the brachial vein using a 23-gauge needle and syringe. Whole blood was immediately transferred to a 2 mL microtube and centrifuged to separate plasma from red blood cells (RBCs). The plasma portion was pipetted into a second microtube and ethanol was added to both tubes. These samples were refrigerated during field trips then stored at −20°C in the laboratory. Seven individuals spontaneously regurgitated prey remains during handling. Prey remains were archived individually and stored at −20°C soon after collection. The small number of regurgitation samples limited capacity for population-wide inference and these results, along with mixing models constructed using isotopic values from regurgitated prey, are provided in an appendix (Appendix Table 2 and Appendix Figures 4, 5, and 6).
Stable isotope analysis and methodological considerations. Various extrinsic and intrinsic factors may influence isotopic values of a consumer. The discrimination factor between a source and a consumer varies with tissue type and species (Caut et al. 2009). However, discrimination factors of blood and feather tissues in piscivorous seabirds have little specific variation (Cherel et al. 2005). Consequently, it is possible to infer respective trophic positions of species by direct comparison of δ15N values.
Isotopic values of feathers indicate dietary assimilation at the time of feather formation (Hobson and Clark 1992), which in frigatebirds occurs during the nonbreeding period (Nelson 1975), estimated to be Dec–Feb in breeding populations in this study. Conversely, RBCs reflect diet 2–4 weeks prior to sampling (Quillfeldt et al. 2008) and plasma reflects integration over the week preceding sampling (Hobson and Clark 1993). Here, RBCs and plasma are indicative of diet during courtship and incubation stages of the breeding cycle.
Feather samples were rinsed in a 2:1 chloroform:methanol bath followed by 2 further rinses in methanol solution. They were air dried for >48 hr and homogenized using scissors and a pizza cutting wheel. The resulting coarse powder was weighed (range: 0.7–0.9 mg) into tin capsules for analysis. Ethanol was evaporated off plasma and RBC samples before being freeze dried, ground, and weighed (range: 0.7–0.9 mg) into tin capsules for analysis. No lipid extraction was undertaken due to the small volume of plasma obtained in some cases. Instead, for tissue-types where the ratio of the mass of carbon to nitrogen was >3.5, we corrected δ13C values using the following equation:Post et al. 2007, Cherel et al. 2014). Feather and RBC samples consistently returned C:N values <3.5 indicating low lipid content and no mathematical correction was applied (Post et al. 2007).
Sample analysis was conducted on an ANCA-GSL2 elemental analyser with resultant CO2 and N2 gases analyzed by a Hydra 20:22 isotope-ratio mass spectrometer (Sercon, Cheshire, UK). Isotopic abundances were derived using the equation δ13C or δ15N = (Rsample/Rstandard) − 1; where R = the ratio of the heavy isotope to light isotope (13C/12C or 15N/14N) in the sample or standard. International standards Vienna Peedee Belemnite and atmospheric N2 were used for carbon and nitrogen isotopic ratios, respectively. All results are presented in delta (δ) notation in per mill (‰) units.
Body mass of sampled birds. Differences in recorded body mass for each species by sex category (hereafter referred to as cohorts) were compared using a one-way ANOVA with pairwise post hoc Tukey HSD tests.
Stable isotope analysis. Reverse sexual dimorphism and interspecies size differences are plausible drivers for variation in foraging behavior. Each cohort was therefore treated as a separate subject group in statistical analysis. Where data conformed to underlying assumptions, a multivariate analysis of variance (MANOVA) test was used to compare means of each cohort. When this overall test indicated that significant differences existed among cohorts, univariate one-way analysis of variance (ANOVA) tests with post hoc Tukey's HSD pairwise comparisons were used for δ13C and δ15N values to attribute causation to a particular cohort or cohorts (e.g., Cherel and Hobson 2007). When necessary, a nonparametric permutational multivariate analysis of variance (PERMANOVA) based on a Euclidean distance similarity index was undertaken using the vegan package in R (e.g., Elsdon et al. 2010). Univariate Kruskal–Wallis tests with pairwise post hoc Nemenyi tests followed where PERMANOVA indicated significant differences were present to determine which cohorts were responsible for the difference. The R package siar (Parnell and Jackson 2013) was used to assess niche overlap between each cohort by constructing standard ellipses. Standard ellipses represent 40% of the data and are equivalent to core isotopic niche. We used the SEAc metric rather than SEA because the former corrects for small sample sizes and loss of an extra degree of freedom associated with analysis of bivariate data (Jackson et al. 2011). Similarity of niche widths was quantified by generating density plots showing credible intervals (50, 75, 95%) of standard ellipse areas in the R package SIBER (Jackson et al. 2011).
Tracking data. Analysis was constrained to tracking data obtained during the early breeding period (March, April, and May). Location data were projected into a Lambert Equal-Area Azimuthal projection and filtered to remove erroneous locations where successive locations required a transit speed exceeding 65 km h−1 (Weimerskirch et al. 2004, Weimerskirch et al. 2010). Filtered data were assigned to individual foraging trips. A foraging trip consisted of any movement beyond the reef platform during which 5 or more locations were recorded (i.e. 20+ min over open ocean). Track segments within the area encompassed by the reef platform were excluded as no foraging activity of frigatebirds has been observed within the reef during fieldwork. Likewise, points within the reef platform of nearby Adele Island were also excluded as these are likely to be associated with short-term roosting/visitation on this island as opposed to foraging activity.
Foraging effort was compared between species by extracting the maximum range, trip duration, path distance, and path sinuosity of each foraging trip using ArcMap 10.3 (ESRI, Redlands, California, USA). Path sinuosity was defined as path distance/(2 × maximum range) with higher values indicating a less linear path. These attributes were compared using mixed effects models with species and sex included as fixed factors and individual included as a random factor. We did not weight data so that each individual contributed an equal amount of data to the analyses. Log10 transformations of the response variable were undertaken when data showed heteroscedasticity or deviations from normality. Likelihood ratio tests were computed for each foraging trip attribute comparing a full model with a null model lacking the fixed factor species to determine whether the effect of species was significant using the lme4 R package. The distal bearing of each foraging trip was extracted using ArcMap. To avoid pseudo-replication only data relating to the distal bearing of the first trip for each individual were included in a Rayleigh test to determine whether orientation of foraging trips was clustered. Mean bearings for foraging trips that had clustered orientations were compared with a Watson–Williams test to indicate whether cohorts oriented trips in a similar direction. This was implemented in R using the package circular.
Kernel density analysis. First passage time (FPT) analysis using the fpt function of the R package adehabitatLT (Calenge 2006) was undertaken to identify the scale at which foraging activity of the tracked birds occurred. This value was used as the bandwidth in kernel density analysis following Lascelles et al. (2016). Core foraging areas (50% utilization distribution) and home range (95% utilization distribution) were constructed for each foraging trip using kernel density analyses in the R package adehabitatHR (Calenge 2006). Individual foraging trips were analyzed independently to remove any influence of convergence of multiple flight paths at the colony.
The habitat attributes sea-surface temperature (SST), chlorophyll-α concentration (Chl-α), and bathymetry were used to determine whether Great Frigatebirds and Lesser Frigatebirds exploited different environmental conditions, thereby facilitating resource partitioning. Eight-day composites of SST and Chl-α data were obtained from NASA's MODIS aqua database (available from the NASA Physical Oceanography Distributed Active Archive Center at http://podaac.jpl.nasa.gov/ and NASA Giovanni Portal at http://giovanni.gsfc.nasa.gov/giovanni/, respectively). These datasets have a resolution of 4 km and SST data represent measurements taken at night. Bathymetric data were obtained from Geoscience Australia's Australian Bathymetry and Topography Grid (Whiteway 2009). The starting date of each foraging trip was used to define which 8-day composite best represented the conditions experienced on that foraging trip.
Outputs of kernel density analysis were imported into ArcMap 10.3 and the median value for each environmental variable within the kernel envelope of individual trips was extracted. For very small kernels that did not contain environmental point data, the nearest point for each variable was manually assigned. To compare environmental variables within kernel areas, linear mixed effects models with species, sex, and environmental variables treated as fixed effects and individual as a random effect were used (Young et al. 2010b, Kappes et al. 2011, Ceia et al. 2015).
All values are reported as means ± SE.
Differences in body mass between cohorts were found (F3,40 = 81.3, P < 0.001). All pairwise post hoc comparisons were significant at the 0.05 level with cohorts assorting from heaviest to lightest in the order female Great Frigatebirds, male Great Frigatebirds, female Lesser Frigatebirds, and male Lesser Frigatebirds (Table 1).
Mean body masses of sampled frigatebird cohorts at Ashmore Reef.
Stable Isotope Analysis
Isotopic values derived from the nonbreeding period (i.e. from feather samples) differed significantly among cohorts (MANOVA: F3,27 = 5.8, P < 0.001) and these were driven by the higher mean δ15N value of male Great Frigatebirds than male Lesser Frigatebirds (P = 0.02) (Figure 2). Male Great Frigatebirds and male Lesser Frigatebirds also had a lower δ13C value than female Lesser Frigatebirds (P = 0.02 and P = 0.03, respectively), but no significant differences were found between these cohorts and female Great Frigatebirds (Figure 2). Analysis of samples indicative of the early breeding season showed that significant differences were driven by higher mean δ15N value of female and male Great Frigatebirds compared to male Lesser Frigatebirds and that this pattern was consistent for both RBC and plasma samples (PERMANOVA; RBC F3,27 = 6.0, P = 0.001; Plasma F3,27 = 6.0, P = 0.001) (Figure 2). For all 3 tissue types, both Great Frigatebird sexes had a higher δ15N value than female Lesser Frigatebirds, but in no case were these differences significant (Figure 2).
Isotopic niche width varied little during the breeding season among cohorts (Figure 3). The smaller niche width of female Lesser Frigatebird plasma samples compared to niche width of plasma samples from male Lesser Frigatebirds was the only significant difference among breeding season samples (Figure 3). Niche width during the nonbreeding period was larger than during the breeding period for all comparisons except female Great Frigatebirds (Figure 3). The niche width of female Great Frigatebird feather samples was smaller in comparison to male Great Frigatebirds and both sexes of Lesser Frigatebird and similar in size to all cohorts during the breeding season (Figure 3). The position of the isotopic niche of male Lesser Frigatebirds did not overlap with either sex of Great Frigatebirds for plasma samples and it did not overlap the isotopic niche of feather samples of female Great Frigatebirds (Figure 2). With the exception of isotopic niches indicated by feather samples of female and male Great Frigatebirds, all other cohorts had some degree of overlap in isotopic niche with greatest overlap between male and female Great Frigatebirds for both breeding season sample types (Figure 2).
Tracking data consisted of 108 trips by 7 Great Frigatebirds (GRFR) and 102 trips by 16 Lesser Frigatebirds (LEFR). There was no difference in mean range of foraging trips (GRFR: 76.4 ± 10.1 km, LEFR: 123.2 ± 10.4 km; χ2 = 3.4, P = 0.07), path distance (GRFR: 364.8 ± 68.9 km, LEFR: 601.1 ± 78.4 km; χ2 = 3.2, P = 0.07), or sinuosity (GRFR: 1.8 ± 0.1, LEFR: 2.0 ± 0.1; χ2 = 2.0, P = 0.16) between species. However Lesser Frigatebirds undertook trips of a significantly longer duration (GRFR: 0.9 ± 0.2 days, LEFR: 1.6 ± 0.2 days; χ2 = 4. 3, P = 0.04).
Foraging trips undertaken by male Great Frigatebirds, and female and male Lesser Frigatebirds, had a clustered orientation (male Great Frigatebird Rayleigh test statistic = 0.62, P < 0.001; female Lesser Frigatebird Rayleigh test statistic = 0.4, P < 0.001; and male Lesser Frigatebird Rayleigh test statistic = 0.6, P = 0.001). Importantly, orientation of these clustered foraging trips was similar (Watson–Williams test F2,128 = 1.9, P = 0.16) across all 3 cohorts with mean bearing of foraging trips centred toward the south-southwest of the colony (male Great Frigatebirds 202.9°; female Lesser Frigatebirds 184.2°; and male Lesser Frigatebirds 215.6°). The distal bearing of foraging trips of female Great Frigatebirds did not display a clustered orientation (Rayleigh test statistic = 0.1, P = 0.65).
Extensive spatial overlap in home range areas used by the 2 species was evident, with 84% of Great Frigatebird home range area occurring within Lesser Frigatebird home range area, whereas 68% of the home range of Lesser Frigatebirds occurred within that of Great Frigatebirds (Figure 1). Areas of core use showed less extensive overlap whereby 43% of Great Frigatebird core area and 41% of Lesser Frigatebird core area occurred within that of the other species (Figure 1).
Median SST within core foraging ranges did not differ between species (χ2 = 0.2, P = 0.67). Core areas of Great Frigatebird foraging trips had significantly higher median Chl-α concentration (χ2 = 11.1, P < 0.001) and were located over waters with shallower bathymetry (χ2 = 6.4, P = 0.01) than core areas of Lesser Frigatebird foraging trips.
Important differences in dietary and spatial aspects of the foraging strategy of Great Frigatebirds and Lesser Frigatebirds were revealed. SIA demonstrated some dietary differences are maintained year-round, whereas tracking and SIA indicated similarity in spatial attributes of foraging during the breeding season. For each tissue type one or both sexes of Great Frigatebird had a higher mean δ15N value compared to male Lesser Frigatebirds. The same trend was apparent, though not significant, for both sexes of Great Frigatebird relative to female Lesser Frigatebirds. Cherel et al. (2008) found similar interspecific differences between δ15N values of Great Frigatebirds and Lesser Frigatebirds during the nonbreeding period, but not the breeding period. They found no significant differences between sexes for Great Frigatebirds and did not test for between-sex differences in Lesser Frigatebirds. Pooling of data across sexes by Cherel et al. (2008) may have contributed to the breeding season disparity between their findings and those presented here.
Year-round Trophic Differences
Our observation that male Lesser Frigatebirds consistently fed on prey with a lower δ15N when compared with other frigatebird cohorts is best explained by body size. Great Frigatebirds are larger than Lesser Frigatebirds (Marchant and Higgins 1990, this study) and frigatebirds display reversed sexual dimorphism (Marchant and Higgins 1990, Lagarde et al. 2004, Mott et al. 2015, this study). Body size can mediate trophic position by enabling larger individuals to capture larger prey items (Cohen et al. 1993, Scharf et al. 2000). In marine food chains, body size of a fish is correlated with its δ15N value and this correlation is particularly strong in flying fish (Mancini et al. 2014, Mancini and Bugoni 2014). Flying fish are a major component of frigatebird diet (Diamond 1975, Harrison et al. 1983, Cherel et al. 2008), a feature confirmed by regurgitation samples obtained here (Appendix Table 2). Therefore, Great Frigatebirds, with their larger body size, may have captured a larger proportion of large-bodied, high δ15N prey items leading to their comparatively high δ15N value. Alternatively, their larger body size may have enabled them to exclude the smaller-bodied Lesser Frigatebird from profitable foraging opportunities and forced Lesser Frigatebirds to forage on a prey base of lower value (Persson 1985, Ballance et al. 1997). However, the smaller number of Great Frigatebirds within the Ashmore study region suggests that it would be difficult to have maintained levels of interference competition sufficient to sustain this effect (Young et al. 2010b). Finally, energetic cost of flight and flight speed of a bird are proportional to body mass and wing loading, respectively (Ellington 1991, Ballance et al. 1997). Although flight costs are low for frigatebirds (Weimerskirch et al. 2003, Weimerskirch et al. 2016), the larger body size of Great Frigatebirds would have incurred higher flight costs relative to the smaller Lesser Frigatebird. In combination with any difference in wing loading between these species, this may have imposed energetic constraints on foraging trips whereby exploiting a foraging location where a prey type or prey size class was particularly abundant was viable for only one of the two species (Shaffer et al. 2001, Phillips et al. 2004, Lewis et al. 2005). Although there are several plausible proximate mechanisms, observed size differences between Great Frigatebirds and Lesser Frigatebirds remain the likely ultimate mechanism leading to differences in resource use. Similar patterns of size-mediated differences in foraging ecology occur in other tropical seabirds (Lewis et al. 2005, Young et al. 2010a, Young et al. 2010b). However, there is no information available to indicate whether body size–mediated differences in prey exploitation we observed occurred in response to limited prey availability or whether these 2 species were simply using prey resources they were best adapted to exploit (Linnebjerg et al. 2013).
Breeding Season Foraging Ecology
Dietary assimilation during the breeding period as inferred through stable isotope analyses (plasma and RBC samples) suggested sampled individuals, irrespective of species or sex, shared similar foraging locations. Similarly, GPS tracking demonstrated striking similarities between foraging strategies of breeding Great Frigatebirds and Lesser Frigatebirds. These conclusions applied to both measures of foraging effort (range, path distance) and spatial usage (home range overlap, clustered orientation of the distal bearing of foraging trips, path sinuosity). Central-place foraging imposes restrictions on foraging range that likely necessitated some degree of spatial convergence in foraging strategy (Phillips et al. 2007). Moreover, these similarities may explain why previous attempts to identify spatial mechanisms facilitating resource partitioning using vessel-based at-sea surveys were unable to resolve interspecific differences (e.g., Pocklington 1979).
Stable isotope analysis and home range estimation are coarse indicators of spatial parameters and coarse-scaled sampling units limit the potential to detect differences in foraging parameters (Haney and Schauer 1994). By contrast, when GPS outputs were considered at the finer resolution of core foraging areas it appears that there were some subtle differences in habitat affinities of the 2 species. Median chlorophyll-α concentration of waters within core foraging areas for both frigatebirds was low relative to the range of chlorophyll-α concentrations available within the foraging range. However, median chlorophyll-α concentration in core areas of Great Frigatebird foraging trips was significantly higher than in core areas of Lesser Frigatebirds. The waters within core foraging areas of Great Frigatebirds also had a significantly shallower median depth. By contrast, in other locations frigatebirds forage preferentially over waters with the highest available productivity (Weimerskirch et al. 2004, Jaquemet et al. 2005, Weimerskirch et al. 2010). Reaching waters with high relative productivity during the present study would have required frigatebirds to depart the colony into a headwind based on prevailing wind conditions (MERRA Model MATMNXSLV v5.2.0 data available from NASA Giovanni Portal at http://giovanni.gsfc.nasa.gov/giovanni/). Many species of seabirds display behaviors that minimize energy expended flying into a headwind (Weimerskirch et al. 2000, Grémillet et al. 2004, Weimerskirch et al. 2005), and frigatebirds may also have oriented foraging trips to capitalize on wind conditions rather than oriented foraging trips toward waters with higher relative productivity (Young et al. 2010b).
Nonbreeding Season Foraging Ecology
Differences in feather sample δ13C values between sexes indicated male frigatebirds include a greater proportion of prey sourced from pelagic locations than female frigatebirds when not breeding (Hobson et al. 1994). This could have resulted from periodic movements over offshore waters or relocation to oceanic islands, whereas females foraged preferentially over inshore waters or relocated to roosting islands in neritic locations. No isoscape information exists for this region to assess the strength of the 13C enrichment gradient between inshore and offshore locations and inform which of these scenarios was most probable. The biennial breeding cycle of frigatebirds that successfully reproduce would result in a large proportion of the population in a nonbreeding phase at any one time (Nelson 1975). Large numbers of nonbreeding birds are not present at this colony during the breeding season (Clarke and Herrod 2014), suggesting post-breeding dispersal from the colony. Migration is a strategy to cope with seasonal variation (Cohen 1967) and post-breeding movements are undertaken by tropical seabirds, including Barau's Petrels (Pterodroma baraui), Cape Verde Shearwaters (Calonectris edwardsii), and Wedge-tailed Shearwaters (Puffinus pacificus) (Catry et al. 2009, González-Solís et al. 2009, Pinet et al. 2011). Cherel et al. (2008) found no difference between the sexes in δ13C value at any stage of the breeding cycle for Great Frigatebirds at Europa Island. Year-round breeding of frigatebirds at Europa Island (Le Corre 2001) indicates that suitable foraging conditions for frigatebirds persist year-round there, possibly negating the need for post-breeding dispersal in that system.
The isotopic niche width of male Great Frigatebirds and male and female Lesser Frigatebirds was larger during the nonbreeding period (feather samples) than the breeding season (plasma and RBC samples) for all cohorts. Although it is important to consider that the time frame over which isotopic information is integrated into feathers differs from red blood cells and plasma, large isotopic niche width during the nonbreeding period occurs in other tropical, and polar, seabird assemblages (Cherel et al. 2007, Cherel et al. 2008). Species including Light-mantled Albatross (Phoebetria palpebrata), Common Diving-Petrel (Pelecanoides urinatrix), and Wilson's Storm-Petrel (Oceanites oceanicus) can have large isotopic variation in feather samples indicative of broad geographical ranges during the nonbreeding period (Cherel et al. 2006, Phillips et al. 2009, Connan et al. 2014). Concomitant trophic differences may also occur, reflecting divergent foraging patterns in different parts of the nonbreeding range (Connan et al. 2014). Broadening of the isotopic niche has been attributed to release from constraints of central-place foraging (Cherel et al. 2007) and results suggest that frigatebirds also increase variation in foraging parameters once breeding has ceased. However, isotopic niche width of female Great Frigatebirds did not increase and this was primarily a result of the low variation in δ13C values within the cohort. Although sample size is small, this suggests low variation in the spatial distribution of this cohort (Ceia et al. 2014), which could be related to habitat specificity during this period.
The results identified dietary partitioning as an important mechanism facilitating year-round partitioning of resources between these congeneric seabirds. When constrained during the breeding season by the requirements of central-place foraging, differences in spatial attributes of the foraging strategy of these species are limited. However, when not breeding, between-sex differences in location of foraging emerge that may further diminish resource overlap among members of this colony.
C. Giuliano, T. Breen, Y. Cherel, J. Pepperell, S. Griffiths, and R. Sellers are thanked for their contribution to identifying regurgitated prey remains. J. Hodgson, S. Baylis, K. Fennessy, and A. Lilleyman provided valuable field assistance. Staff of Diversity Charter Company and Kimberley Expeditions are thanked for their professional service during vessel transit. R. Woodland provided comment on a draft of this manuscript, as did 2 anonymous referees.
Funding statement: This work was supported by funding from BirdLife Australia's Stuart Leslie Bird Research Award, the Holsworth Wildlife Research Endowment, and the Paddy Pallin Foundation.
Ethics statement: All research was conducted under Monash University Animal Ethics (permit number: BSCI/2012/08) and Wildlife Research (permit numbers: AU-COM2012-138 and E2011-0059) permits.
Author contributions: R.M. and R.H.C. conceived the experimental design and methods. R.M. and A.H. performed the experiments. R.M. analyzed the data. R.M., R.H.C., and A.H. wrote the paper.
- Ainley, D. G., and R. J. Boekelheide (1984). An ecological comparison of oceanic seabird communities of the South Pacific Ocean. InTropical Seabird Biology ( R. W. Schreiber, Editor). Studies in Avian Biology 8:2–23. Google Scholar
- Allen, G. R., R. Swainston, and J. Ruse (2009). Field Guide to Marine Fishes of Tropical Australia and South-East Asia. Western Australian Museum, Perth, Western Australia. Google Scholar
- Ashmole, N. P. (1963). The regulation of numbers of tropical oceanic birds. Ibis 103b:458–473. Google Scholar
- Ashmole, N. P., and M. J. Ashmole (1967). Comparative Feeding Ecology of Sea Birds of a Tropical Oceanic Island. Peabody Museum of Natural History, Yale University, Bulletin 24. New Haven, CT, USA. Google Scholar
- Au, D. W. K., and R. L. Pitman (1986). Seabird interactions with dolphins and tuna in the eastern tropical Pacific. The Condor 88:304–317. Google Scholar
- Ballance, L. T., R. L. Pitman, and S. B. Reilly (1997). Seabird community structure along a productivity gradient: Importance of competition and energetic constraint. Ecology 78:1502–1518. Google Scholar
- Bearhop, S., C. E. Adams, S. Waldron, R. A. Fuller, and H. MacLeod (2004). Determining trophic niche width: A novel approach using stable isotope analysis. Journal of Animal Ecology 73:1007–1012. Google Scholar
- BirdLife International. 2013. Important Bird Areas factsheet: Ashmore Reef. http://www.birdlife.org/datazone/sitefactsheet.php?id=23948. Google Scholar
- Birt, V. L., T. P. Birt, D. Goulet, D. K. Cairns, and W. A. Montevecchi (1987). Ashmole's halo: Direct evidence for prey depletion by a seabird. Marine Ecology Progress Series 40:205–208. Google Scholar
- Brewer, M. L., and F. Hertel (2007). Wing morphology and flight behavior of pelecaniform seabirds. Journal of Morphology 268:866–877. Google Scholar
- Calenge, C. (2006). The package adehabitat for the R software: A tool for the analysis of space and habitat use by animals. Ecological Modelling 197:516–519. Google Scholar
- Catry, T., J. A. Ramos, M. Le Corre, and R. A. Phillips (2009). Movements, at-sea distribution and behaviour of a tropical pelagic seabird: The Wedge-tailed Shearwater in the western Indian Ocean. Marine Ecology Progress Series 391:231–242. Google Scholar
- Caut, S., E. Angulo, and F. Courchamp (2009). Variation in discrimination factors (Δ15N and Δ13C): The effect of diet isotopic values and applications for diet reconstruction. Journal of Applied Ecology 46:443–453. Google Scholar
- Ceia, F. R., V. H. Paiva, R. S. Ceia, S. Hervías, S. Garthe, J. C. Marques, and J. A. Ramos (2015). Spatial foraging segregation by close neighbours in a wide-ranging seabird. Oecologia 177:431–440. Google Scholar
- Ceia, F. R., V. H. Paiva, S. Garthe, J. C. Marques, and J. A. Ramos (2014). Can variations in the spatial distribution at sea and isotopic niche width be associated with consistency in the isotopic niche of a pelagic seabird species?Marine Biology 161:1861–1872. Google Scholar
- Chaurand, T., and H. Weimerskirch (1994). The regular alternation of short and long foraging trips in the Blue Petrel Halobaena caerulea: A previously undescribed strategy of food provisioning in a pelagic seabird. Journal of Animal Ecology 63:275–282. Google Scholar
- Chen, X., H. Lu, B. Liu, Y. Chen, S. Li, and M. Jin (2012). Species identification of Ommastrephes bartramii, Dosidicus gigas, Sthenoteuthis oualaniensis and Illex argentinus (Ommastrephidae) using beak morphological variables. Scientia Marina 76:473–481. Google Scholar
- Cherel, Y., and K. A. Hobson (2007). Geographical variation in carbon stable isotope signatures of marine predators: A tool to investigate their foraging areas in the Southern Ocean. Marine Ecology Progress Series 329:281–287. Google Scholar
- Cherel, Y., K. A. Hobson, C. Guinet, and C. Vanpe (2007). Stable isotopes document seasonal changes in trophic niches and winter foraging individual specialization in diving predators from the Southern Ocean. Journal of Animal Ecology 76:826–836. Google Scholar
- Cherel, Y., K. A. Hobson, and S. Hassani (2005). Isotopic discrimination between food and blood and feathers of captive penguins: Implications for dietary studies in the wild. Physiological and Biochemical Zoology 78:106–115. Google Scholar
- Cherel, Y., M. Connan, A. Jaeger, and P. Richard (2014). Seabird year-round and historical feeding ecology: Blood and feather δ13C and δ15N values document foraging plasticity of small sympatric petrels. Marine Ecology Progress Series 505:267–280. Google Scholar
- Cherel, Y., M. Le Corre, S. Jaquemet, F. Menard, P. Richard, and H. Weimerskirch (2008). Resource partitioning within a tropical seabird community: New information from stable isotopes. Marine Ecology Progress Series 366:281–291. Google Scholar
- Cherel, Y., R. A. Phillips, K. A. Hobson, and R. McGill (2006). Stable isotope evidence of diverse species-specific and individual wintering strategies in seabirds. Biology Letters 2:301–303. Google Scholar
- Clarke, R. H., and A. Herrod (2014). Seabirds and shorebirds at Ashmore Reef, Cartier Island & Browse Island. Monitoring Program for the Montara Well Release, Ninth Post-impact Field Survey Data Summary and Progress Report. Unpublished report, Monash University, Melbourne, Australia. Google Scholar
- Clarke, R. H., M. Carter, G. Swann, and J. Thomson (2011). The status of breeding seabirds and herons at Ashmore Reef, off the Kimberley coast, Australia. Journal of the Royal Society of Western Australia 94:171–182. Google Scholar
- Cohen, D. (1967). Optimization of seasonal migratory behavior. The American Naturalist 101:5–17. Google Scholar
- Cohen, J. E., S. L. Pimm, P. Yodzis, and J. Saldaña (1993). Body sizes of animal predators and animal prey in food webs. Journal of Animal Ecology 62:67–78. Google Scholar
- Connan, M., C. D. McQuaid, B. T. Bonnevie, M. J. Smale, Y. Cherel, and N. Klages (2014). Combined stomach content, lipid and stable isotope analyses reveal spatial and trophic partitioning among three sympatric albatrosses from the Southern Ocean. Marine Ecology Progress Series 497:259–272. Google Scholar
- Cooke, S. J., S. G. Hinch, M. Wikelski, R. D. Andrews, L. J. Kuchel, T. G. Wolcott, and P. J. Butler (2004). Biotelemetry: A mechanistic approach to ecology. Trends in Ecology & Evolution 19:334–343. Google Scholar
- Diamond, A. (1975). Biology and behaviour of frigatebirds Fregata spp. on Aldabra Atoll. Ibis 117:302–323. Google Scholar
- Dunlop, J. N., C. A. Surman, and R. D. Wooller (2001). The marine distribution of seabirds from Christmas Island, Indian Ocean. Emu 101:19–24. Google Scholar
- Egevang, C., I. J. Stenhouse, R. A. Phillips, A. Petersen, J. W. Fox, and J. R. D. Silk (2010). Tracking of Arctic terns Sterna paradisaea reveals longest animal migration. Proceedings of the National Academy of Sciences USA 107:2078–2081. Google Scholar
- Ellington, C. (1991). Limitations on animal flight performance. Journal of Experimental Biology 160:71–91. Google Scholar
- Elliott, K. H., K. J. Woo, A. J. Gaston, S. Benvenuti, L. Dall'Antonia, and G. K. Davoren (2009). Central-place foraging in an Arctic seabird provides evidence for Storer-Ashmole's halo. The Auk 126:613–625. Google Scholar
- Elsdon, T. S., S. Ayvazian, K. W. McMahon, and S. R. Thorrold (2010). Experimental evaluation of stable isotope fractionation in fish muscle and otoliths. Marine Ecology Progress Series 408:195–205. Google Scholar
- Food and Agriculture Organization of the United Nations (1974). FAO species identification sheets for fishery purposes: Eastern Indian Ocean Fishing Area 57 and Western Central Pacific Fishing Area 71. Food and Agriculture Organization of the United Nations, Rome, Italy. Google Scholar
- Furlani, D., R. Gales, and D. Pemberton (2007). Otoliths of Common Australian Temperate Fish: A Photographic Guide. CSIRO publishing, Collingwood, Australia. Google Scholar
- Furness, R. W., and T. R. Birkhead (1984). Seabird colony distributions suggest competition for food supplies during the breeding season. Nature 311:655–656. Google Scholar
- Gause, G. F. (1934). The Struggle for Existence. Williams & Wilkins Co., Baltimore, MD, USA. Google Scholar
- González-Solís, J., Á. M. Felicísimo, J. W. Fox, V. Afanasyev, Y. Kolbeinsson, and J. Muñoz (2009). Influence of sea surface winds on shearwater migration detours. Marine Ecology Progress Series 391:221–230. Google Scholar
- González-Solís, J., J. P. Croxall, and A. G. Wood (2000). Sexual dimorphism and sexual segregation in foraging strategies of Northern Giant Petrels, Macronectes halli, during incubation. Oikos 90:390–398. Google Scholar
- González-Solís, J., J. P. Croxall, D. Oro, and X. Ruiz (2007). Trans-equatorial migration and mixing in the wintering areas of a pelagic seabird. Frontiers in Ecology and the Environment 5:297–301. Google Scholar
- Grémillet, D., G. Dell'Omo, P. G. Ryan, G. Peters, Y. Ropert-Coudert, and S. J. Weeks (2004). Offshore diplomacy, or how seabirds mitigate intra-specific competition: A case study based on GPS tracking of Cape Gannets from neighbouring colonies. Marine Ecology Progress Series 268:265–279. Google Scholar
- Haney, J. C., and A. E. S. Schauer (1994). Environmental variability facilitates coexistence within an alcid community at sea. Marine Ecology Progress Series 103. Google Scholar
- Hardin, G. (1960). The Competitive Exclusion Principle. Science 131:1292–1297. Google Scholar
- Harrison, C. S., T. S. Hida, and M. P. Seki (1983). Hawaiian seabird feeding ecology. Wildlife Monographs 85:3–71. Google Scholar
- Henkel, L. A. (2009). Co-occurrence and aggregation of marine birds and mammals in Monterey Bay, California, USA. Marine Ecology Progress Series 387:295–303. Google Scholar
- Hobson, K. A., and R. G. Clark (1992). Assessing avian diets using stable isotopes I: Turnover of 13C in tissues. The Condor:181–188. Google Scholar
- Hobson, K. A., and R. G. Clark (1993). Turnover of 13C in cellular and plasma fractions of blood: Implications for nondestructive sampling in avian dietary studies. The Auk 110:638–641. Google Scholar
- Hobson, K. A., J. F. Piatt, and J. Pitocchelli (1994). Using stable isotopes to determine seabird trophic relationships. Journal of Animal Ecology 63:786–798. Google Scholar
- Hutchinson, G. E. (1959). Homage to Santa Rosalia or why are there so many kinds of animals?The American Naturalist 93:145–159. Google Scholar
- Inger, R., and S. Bearhop (2008). Applications of stable isotope analyses to avian ecology. Ibis 150:447–461. Google Scholar
- Jackson, A. L., R. Inger, A. C. Parnell, and S. Bearhop (2011). Comparing isotopic niche widths among and within communities: SIBER – Stable Isotope Bayesian Ellipses in R. Journal of Animal Ecology 80:595–602. Google Scholar
- Jackson, A. L., R. Inger, S. Bearhop, and A. Parnell (2009). Erroneous behaviour of MixSIR, a recently published Bayesian isotope mixing model: A discussion of Moore & Semmens (2008). Ecology Letters 12:E1–E5. Google Scholar
- James, D. J., and I. A. W. McAllan (2014). The birds of Christmas Island, Indian Ocean: A review. Australian Field Ornithology 31:S1–S175. Google Scholar
- Jaquemet, S., M. Le Corre, F. Marsac, M. Potier, and H. Weimerskirch (2005). Foraging habitats of the seabird community of Europa Island (Mozambique Channel). Marine Biology 147:573–582. Google Scholar
- Jessopp, M. J., M. Cronin, T. K. Doyle, M. Wilson, A. McQuatters-Gollop, S. Newton, and R. A. Phillips (2013). Transatlantic migration by post-breeding puffins: A strategy to exploit a temporarily abundant food resource?Marine Biology 160:2755–2762. Google Scholar
- Kappes, M. A., H. Weimerskirch, D. Pinaud, and M. Le Corre (2011). Variability of resource partitioning in sympatric tropical boobies. Marine Ecology Progress Series 441:281–294. Google Scholar
- King, B. R. (1986). Seabird Islands: Raine Island, Great Barrier Reef, Queensland. Corella 10:73–77. Google Scholar
- Lagarde, F., H. Lormee, and M. Le Corre (2004). Parental care in frigatebirds: A comparison between two sympatric species. Revue d'Ecologie-La Terre et la Vie 59:465–474. Google Scholar
- Lascelles, B. G., P. R. Taylor, M. G. R. Miller, M. P. Dias, S. Oppel, L. Torres, A. Hedd, M. Le Corre, R. A. Phillips, S. A. Shaffer, H. Weimerskirch, and C. Small (2016). Applying global criteria to tracking data to define important areas for marine conservation. Diversity and Distributions 22:422–431. Google Scholar
- Le Corre, M. (2001). Breeding seasons of seabirds at Europa Island (southern Mozambique Channel) in relation to seasonal changes in the marine environment. Journal of Zoology 254:239–249. Google Scholar
- Lewis, S. U. E., E. A. Schreiber, F. Daunt, G. A. Schenk, K. Orr, A. Adams, S. Wanless, and K. C. Hamer (2005). Sex-specific foraging behaviour in tropical boobies: Does size matter?Ibis 147:408–414. Google Scholar
- Lewis, S., T. N. Sherratt, K. C. Hamer, and S. Wanless (2001). Evidence of intra-specific competition for food in a pelagic seabird. Nature 412:816–819. Google Scholar
- Linnebjerg, J. F., A. Reuleaux, K. N. Mouritsen, and M. Frederiksen (2015). Foraging ecology of three sympatric breeding alcids in a declining colony in southwest Greenland. Waterbirds 38:143–152. Google Scholar
- Logan, J. M., T. D. Jardine, T. J. Miller, S. E. Bunn, R. A. Cunjak, and M. E. Lutcavage (2008). Lipid corrections in carbon and nitrogen stable isotope analyses: Comparison of chemical extraction and modelling methods. Journal of Animal Ecology 77:838–846. Google Scholar
- Lu, C. C., and R. Ickeringill (2002). Cephalopod beak identification and biomass estimation techniques: Tools for dietary studies of southern Australian finfishes. Museum Victoria Science Reports 6:1–65. Google Scholar
- MacArthur, R. H. (1957). On the relative abundance of bird species. Proceedings of the National Academy of Sciences USA 43:293–295. Google Scholar
- Macarthur, R., and R. Levins (1967). The limiting similarity, convergence, and divergence of coexisting species. The American Naturalist 101:377–385. Google Scholar
- Mahoney, S. A. (1984). Plumage wettability of aquatic birds. The Auk 101:181–185. Google Scholar
- Mancini, P. L., and L. Bugoni (2014). Resources partitioning by seabirds and their relationship with other consumers at and around a small tropical archipelago. ICES Journal of Marine Science 71:2599–2607. Google Scholar
- Mancini, P. L., K. A. Hobson, and L. Bugoni (2014). Role of body size in shaping the trophic structure of tropical seabird communities. Marine Ecology Progress Series 497:243–257. Google Scholar
- Marchant, S., and P. J. Higgins (1990). Handbook of Australian, New Zealand and Antarctic Birds, Vol. 1: Ratites to Ducks. Oxford University Press, Melbourne, Victoria, Australia. Google Scholar
- McKnight, A., A. J. Allyn, D. C. Duffy, and D. B. Irons (2013). ‘Stepping stone' pattern in Pacific Arctic tern migration reveals the importance of upwelling areas. Marine Ecology Progress Series 491:253–264. Google Scholar
- Mott, R., A. Herrod, J. C. Hodgson, and R. H. Clarke (2015). An evaluation of the use of predicted harness spans for correctly fitting leg loop harnesses in seabird research. Waterbirds 38:420–424. Google Scholar
- Nateewathana, A. (1992). Taxonomic studies on loliginid squids (Cephalopoda: Loliginidae) from the Andaman Sea coast of Thailand. Phuket Marine Biological Centre Research Bulletin 57:1–40. Google Scholar
- Nelson, J. B. (1975). The breeding biology of frigatebirds: A comparative review. Living Bird 14:113–155. Google Scholar
- Norman, M., and A. Reid (2000). A Guide to Squid, Cuttlefish and Octopuses of Australasia. CSIRO Publishing, Collingwood, Victoria, Australia. Google Scholar
- Orta, J. (1992). Family Fregatidae (Frigatebirds). In Handbook of the Birds of the World, vol. 1: Ostrich to Ducks ( J. del Hoyo, Elliott, A. and J. Sargatal, Editors). Lynx Edicions, Barcelona, Spain.pp. 1362–1374. Google Scholar
- Persson, L. (1985). Asymmetrical competition: Are larger animals competitively superior?The American Naturalist 126:261–266. Google Scholar
- Phillips, R. A., J. P. Croxall, J. R. D. Silk, and D. R. Briggs (2007). Foraging ecology of albatrosses and petrels from South Georgia: Two decades of insights from tracking technologies. Aquatic Conservation: Marine and Freshwater Ecosystems 17:S6–S21. Google Scholar
- Phillips, R. A., J. R. D. Silk, B. Phalan, P. Catry, and J. P. Croxall (2004). Seasonal sexual segregation in two Thalassarche albatross species: Competitive exclusion, reproductive role specialization or foraging niche divergence?Proceedings of the Royal Society of London, Series B 271:1283–1291. Google Scholar
- Phillips, R. A., S. Bearhop, R. A. Mcgill, and D. A. Dawson (2009). Stable isotopes reveal individual variation in migration strategies and habitat preferences in a suite of seabirds during the nonbreeding period. Oecologia 160:795–806. Google Scholar
- Pinet, P., S. Jaquemet, D. Pinaud, H. Weimerskirch, R. A. Phillips, and M. Le Corre (2011). Migration, wintering distribution and habitat use of an endangered tropical seabird, Barau's Petrel Pterodroma baraui. Marine Ecology Progress Series 423:291–302. Google Scholar
- Pocklington, R. (1979). An oceanographic interpretation of seabird distributions in the Indian Ocean. Marine Biology 51:9–21. Google Scholar
- Post, D. M., C. A. Layman, D. A. Arrington, G. Takimoto, J. Quattrochi, and C. G. Montaña (2007). Getting to the fat of the matter: Models, methods and assumptions for dealing with lipids in stable isotope analyses. Oecologia 152:179–189. Google Scholar
- Quillfeldt, P., L. Bugoni, R. R. McGill, J. Masello, and R. Furness (2008). Differences in stable isotopes in blood and feathers of seabirds are consistent across species, age and latitude: Implications for food web studies. Marine Biology 155:593–598. Google Scholar
- Rayner, M. J., M. E. Hauber, M. N. Clout, D. S. Seldon, S. Van Dijken, S. Bury, and R. A. Phillips (2008). Foraging ecology of the Cook's Petrel Pterodroma cookii during the austral breeding season: A comparison of its two populations. Marine Ecology Progress Series 370:271–284. Google Scholar
- Ropert-Coudert, Y., and R. P. Wilson (2005). Trends and perspectives in animal-attached remote sensing. Frontiers in Ecology and the Environment 3:437–444. Google Scholar
- Scharf, F. S., F. Juanes, and R. A. Rountree (2000). Predator size–prey size relationships of marine fish predators: Interspecific variation and effects of ontogeny and body size on trophic-niche breadth. Marine Ecology Progress Series 208:229–248. Google Scholar
- Shaffer, S. A., H. Weimerskirch, and D. P. Costa (2001). Functional significance of sexual dimorphism in Wandering Albatrosses, Diomedea exulans. Functional Ecology 15:203–210. Google Scholar
- Smith, J. A., D. Mazumder, I. M. Suthers, and M. D. Taylor (2013). To fit or not to fit: Evaluating stable isotope mixing models using simulated mixing polygons. Methods in Ecology and Evolution 4:612–618. Google Scholar
- Spear, L. B., D. G. Ainley, and W. A. Walker (2007). Foraging Dynamics of Seabirds in the Eastern Tropical Pacific Ocean. Studies in Avian Biology, no. 35. Google Scholar
- Stauss, C., S. Bearhop, T. Bodey, S. Garthe, C. Gunn, W. Grecian, R. Inger, M. Knight, J. Newton, and S. Patrick (2012). Sex-specific foraging behaviour in Northern Gannets Morus bassanus: Incidence and implications. Marine Ecology Progress Series 457:151–162. Google Scholar
- Steenweg, R. J., R. A. Ronconi, and M. L. Leonard (2011). Seasonal and age-dependent dietary partitioning between the Great Black-backed and Herring gulls. The Condor 113:795–805. Google Scholar
- Wakefield, E. D., T. W. Bodey, S. Bearhop, J. Blackburn, K. Colhoun, R. Davies, R. G. Dwyer, J. Green, D. Grémillet, A. L. Jackson, M. J. Jessopp, et al. (2013). Space partitioning without territoriality in gannets. Science 341:68–70. Google Scholar
- Weimerskirch, H. (1998). How can a pelagic seabird provision its chick when relying on a distant food resource? Cyclic attendance at the colony, foraging decision and body condition in Sooty Shearwaters. Journal of Animal Ecology 67:99–109. Google Scholar
- Weimerskirch, H. (2007). Are seabirds foraging for unpredictable resources?Deep Sea Research Part II: Topical Studies in Oceanography 54:211–223. Google Scholar
- Weimerskirch, H., C. Bishop, T. Jeanniard-du-Dot, A. Prudor, and G. Sachs (2016). Frigate birds track atmospheric conditions over months-long transoceanic flights. Science 353:74–78. Google Scholar
- Weimerskirch, H., J. A. Bartle, P. Jouventin, and J. C. Stahl (1988). Foraging ranges and partitioning of feeding zones in three species of southern albatrosses. The Condor 90:214–219. Google Scholar
- Weimerskirch, H., M. L. Corre, Y. Ropert-Coudert, A. Kato, and F. Marsac (2005). The three-dimensional flight of Red-footed Boobies: Adaptations to foraging in a tropical environment?Proceedings of the Royal Society of London, Series B 272:53–61. Google Scholar
- Weimerskirch, H., M. Le Corre, E. T. Kai, and F. Marsac (2010). Foraging movements of Great Frigatebirds from Aldabra Island: Relationship with environmental variables and interactions with fisheries. Progress in Oceanography 86:204–213. Google Scholar
- Weimerskirch, H., M. Le Corre, S. Jaquemet, M. Potier, and F. Marsac (2004). Foraging strategy of a top predator in tropical waters: Great Frigatebirds in the Mozambique Channel. Marine Ecology Progress Series 275:297–308. Google Scholar
- Weimerskirch, H., O. Chastel, C. Barbraud, and O. Tostain (2003). Flight performance: Frigatebirds ride high on thermals. Nature 421:333–334. Google Scholar
- Weimerskirch, H., T. Guionnet, J. Martin, S. Shaffer, and D. Costa (2000). Fast and fuel efficient? Optimal use of wind by flying albatrosses. Proceedings of the Royal Society of London, Series B 267:1869–1874. Google Scholar
- Whiteway, T. (2009). Australian bathymetry and topography grid, June 2009. Scale 1:5000000. Geoscience Australia, Canberra, Australia. Google Scholar
- Wolff, G. A. (1982). A beak key for eight eastern tropical Pacific cephalopod species with relationships between their beak dimensions and size. Fishery Bulletin 80:357–370. Google Scholar
- Wolff, G. A. (1984). Identification and estimation of size from the beaks of 18 species of cephalopods from the Pacific Ocean. NOAA Technical Report NMFS 17. U.S. Department of Commerce, Springfield, VA, USA. Google Scholar
- Xavier, J. C., and Y. Cherel (2009). Cephalopod Beak Guide for the Southern Ocean. British Antarctic Survey, Cambridge, UK. Google Scholar
- Young, H. S., D. J. McCauley, R. Dirzo, R. B. Dunbar, and S. A. Shaffer (2010a). Niche partitioning among and within sympatric tropical seabirds revealed by stable isotope analysis. Marine Ecology Progress Series 416:285–294. Google Scholar
- Young, H. S., S. A. Shaffer, D. J. McCauley, D. G. Foley, R. Dirzo, and B. A. Block (2010b). Resource partitioning by species but not sex in sympatric boobies in the central Pacific Ocean. Marine Ecology Progress Series 403:291–301. Google Scholar
Identification of Regurgitated Prey Remains
Each regurgitated prey item was identified to the lowest taxonomic unit possible. Food and Agriculture Organization species identification sheets (Food and Agriculture Organization of the United Nations 1974), Allen et al. (2009), the online resource Fishbase (available at http://www.fishbase.org), and a photographic reference collection of known identity prey remains were used to assist visual identification. Identification of otoliths involved comparison with a reference collection extracted from fish of known identity and the resources of Furlani et al. (2007) and Fishbase. Cephalopod beaks were identified primarily using Lu and Ickeringill (2002), but also Wolff (1982, 1984), Nateewathana (1992), Xavier and Cherel (2009), and Chen et al. (2012). Cuttlebones were identified using Norman and Reid (2000). It was not possible to identify all ingested items to species level due to partial digestion of some items and results are subsequently grouped at the family level.
The importance of individual taxa in the diet of frigatebird species was assessed by calculating frequency of occurrence and numerical abundance (Polito et al. 2011, Connan et al. 2014). Frequency of occurrence was calculated as the proportion of regurgitation samples that contained the given prey. Numerical abundance was calculated as the total number of individuals of a given prey taxon across all regurgitation samples as a percentage of the total number of identified prey items.
Results of Identification of Prey Remains
Exocoetid and hemiramphid fishes were present in both Great and Lesser frigatebird regurgitate samples (Appendix Table 2). Piscivorous predators of the families Scombridae and Carangidae were present only in regurgitate samples of Great Frigatebirds (Appendix Table 2). Conversely, remains of ommastrephid squid were present only in Lesser Frigatebird regurgitate samples (Appendix Table 2).
Regurgitation sample preparation for stable isotope analysis. Regurgitated remains of prey from 5 families that occur most frequently in regurgitation samples of frigatebirds in this region were subjected to SIA (hemiramphids were not included because of limited undigested tissue). Sample preparation followed Logan et al. (2008). A sample of muscle was removed from the caudal region of fish or the mantle of cephalopods. Samples were rinsed in deionized water before being finely minced and oven-dried at 60°C for 48 hr until constant mass was attained. Dried samples were then ground with a mortar and pestle and the resulting powder separated into 2 subsamples per prey item. The first set of subsamples was immediately prepared for SIA (referred to hereafter as bulk samples), whereas other subsamples were subjected to a lipid extraction. Lipid extraction consisted of immersing the sample in a 2:1 chloroform:methanol solution, mixing by vortexing for 30 s before standing for 30 min. Each sample was subsequently centrifuged at 1318 g for 10 min and the supernatant was discarded with the aid of a pipette. This immersion process was repeated 3 or more times until the supernatant was no longer colored or cloudy. Lipid extracted samples were again oven dried at 60°C for 48 hr. Bulk samples and lipid extracted samples were freeze dried and weighed (range: 0.4–0.6 mg) into tin capsules for analysis.
Mixing model generation. Stable isotopic values obtained from regurgitated prey remains commonly occurring in the diet of frigatebirds were used to estimate proportional contribution of prey families to the diet of Lesser and Great frigatebirds. This was achieved using mixing models solved within the SIAR Bayesian framework with a non-informative Dirichlet prior distribution (Jackson et al. 2009) and Markov chain Monte Carlo (MCMC) simulations. SIAR mixing models generate a true probability density function for the parameter of interest. Default SIAR MCMC parameters (iterations = 2 105, burning = 5 104, thinning = 15) were used for modelling. No trophic enrichment factor has been determined for any species of frigatebird so we applied the values of Stauss et al. (2012) to mixing models for another Suliform seabird, the Northern Gannet (Morus bassanus). These were Δ13C = +0.24 (±0.79) and Δ15N = +2.25 (±0.61). Simulated mixing polygons were generated following Smith et al. (2013) using the packages sp and splancs in program R to make an a priori assessment of the goodness-of-fit of the data to the mixing model. No sampled birds were excluded as all were within the 0.05 contour (Appendix Figure 4) indicating that a viable mathematical solution for the mixing model existed (Smith et al. 2013).
Mixing model outputs. In relation to among-group separation, variation in isotopic value of all 5 prey families considered was large in both the δ13C and δ15N directions resulting in substantial overlap in the spread of samples (Appendix Figure 5) and a mixing model with little discriminating power. Consequently the model indicated approximately equal contributions of each prey family to the diet of males and females of both species (Appendix Figure 6).