AbstractTiger sharks (Galeocerdo cuvier) are typically solitary marine predators that are rarely observed forming aggregations. We analyzed long-term acoustic telemetry data from the Hawaiian Archipelago that indicate that there are seasonal partial migrations within the population. We investigated whether these migrations are driven primarily by mating or foraging behaviors. Mature tiger sharks tagged around O ‘ahu migrated seasonally to Maui, with timing aligned with the known mating season in Hawai ‘i. In contrast, sharks tagged around Maui displayed year-round residency (no seasonal departures). Seasonal philopatry was most pronounced at Olowalu, Maui. At this site, we observed a high spatiotemporal overlap between mature males and females and physical signs of mating activity for both sexes, which suggested a mating aggregation. Shark abundance at Olowalu peaked approximately one month prior to the peak presence of adult humpback whales (Megaptera novaeangliae). Whale calf abundance was moderately correlated with shark detection rates, suggesting that foraging opportunities might also influence the timing of shark aggregations. These aggregations appear diffuse rather than dense, extending over several kilometers and persisting for several weeks. Our findings provide the first evidence of potential seasonal mating aggregations in tiger sharks, a behavior previously undocumented for this typically solitary species.
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IntroductionTiger sharks (Galeocerdo cuvier) are marine top predators that play a crucial role in ecosystem function across their temperate and tropical circumglobal distribution1,2,3. By regulating prey abundance and behavior, suppressing mesopredators, scavenging large carrion, and transporting nutrients across habitats, they influence community structure and cross-ecosystem energy flow4,5. They are typically solitary in nature and rarely form aggregations except in the context of feeding events or possibly in gestation-related groupings6,7,8,9,10,11. Significant knowledge gaps remain in our understanding of their spatial ecology, especially regarding seasonal movements, reproductive behavior, and the occurrence of aggregations3. Although tiger sharks are known to mate seasonally12,13 it is unclear whether mating relies on opportunistic encounters between males and females, whether they aggregate at specific sites, or whether both factors contemporaneously drive their reproductive strategies. This lack of understanding complicates the identification of key habitats and hinders the prediction of behaviors that are important for informing their conservation and management.Meyer et al.14 observed increases in tiger shark presence around Maui that align with the mid-winter mating season, suggesting a possible link to reproductive behavior. However, the observed detection peaks may instead reflect foraging, as tiger sharks in other regions aggregate in response to seasonal prey pulses such as fledgling seabirds and nesting sea turtles5,15. Waters surrounding Maui also experience an influx of humpback whales (Megaptera novaeangliae) during the winter months16, offering potential seasonal scavenging opportunities from whale carcasses, placental remains, or neonate calves17,18,19. The coincidence of Hawaiʻi’s tiger shark mating season with the humpback whale arrival period makes it difficult to distinguish movements driven by mating from those linked to whale-related foraging.Meyer et al.14tagged tiger sharks with long-lasting acoustic tags, collecting a continuous six-year time series of detections around Maui and O ‘ahu from 2013 to 2019. This extensive dataset provides an unprecedented opportunity to assess whether seasonal movements to Maui are driven by mating, by foraging, or a combination of the two, as these may not be mutually exclusive activities. Tiger sharks could utilize the shelf of Maui Nui (the region encompassing the islands of Maui, Moloka ‘i, Lānaʻi, and Kahoʻolawe), for both purposes, and both could produce similar patterns of acoustic detections (i.e. clusters of individuals in space and time). The maturity status of the sharks present, as well as the temporal predictability of the clusters could provide further insight into the function of these aggregations. For example, a mating aggregation requires sexually mature adults of both sexes to be present simultaneously at a predictable time each year (tiger shark size at first reproduction: males ~ 292 cm TL, females ~ 330 cm TL13;). In contrast, a cluster of detections consisting of only one sex and/or immature individuals that closely tracks prey abundance may be more indicative of foraging activity.In this study we addressed five questions: (1) Do tiger sharks tagged around O ‘ahu and Maui exhibit repeated inter-island movements? (2) Are these movements seasonal? (3) What are the demographics of seasonal inter-island migrants? (4) Do specific Maui sites show seasonal shark aggregations and overlapping use by both sexes? (5) Does tiger shark seasonal presence correlate with humpback whale indicators (song intensity and calf counts)? By addressing these questions, we aim to clarify the ecological drivers behind tiger shark movements and possible aggregations, thereby advancing our understanding of tiger shark behavior and identifying potentially important habitats in the Hawaiian Islands.MethodsStudy siteThe Main Hawaiian Islands (MHI) consist of eight high volcanic islands. Shark capture and tagging efforts in this study were concentrated around O ‘ahu and Maui (Fig. 1). The MHI are each bordered by an insular shelf that gradually descends from the shoreline to a shelf break, occurring at depths between 100 and 200 m (Fig. 1). The width of this insular shelf differs across the islands, with the Maui Nui complex (Maui, Moloka ‘i, Lānaʻi, and Kahoʻolawe) having a more extensive shelf than the islands of Ni ‘ihau, Kaua ‘i, O ‘ahu, and Hawai ‘i combined (Fig. 1). The insular shelf hosts a variety of photic and mesophotic coral reefs, macroalgal beds, and sandy habitats20,21, and is the preferred habitat for tiger sharks in Hawaii waters14.Fig. 1Bathymetry of the Main Hawaiian Islands highlighting the insular shelf between depths of zero and 200 m (red shaded areas).Full size imageOlowalu, on Maui’s west coast (Fig. 2), features a diverse benthic habitat (coral reefs, sandy bottom, macroalgal beds) and a gentle slope to ~ 60 m depth22,23,24. Importantly, Olowalu’s sheltered waters host breeding, calving, and nursing humpback whales during their overwintering period25,26,27, making it an important seasonal habitat for this whale population.Fig. 2Receiver locations (red diamonds) around Maui (a) and O ‘ahu (b). Six sites with the most consistent temporal coverage are represented by solid filled red diamonds.Full size imageAcoustic monitoring systemWe used Vemco VR2W acoustic receivers (69 kHz frequency) to monitor tiger shark presence around Maui and O ‘ahu. These small, self-contained underwater receivers (∼ 34 cm length, 6 cm diameter) detect coded acoustic transmitters. Each tagged shark carried a V16-6H transmitter (16 × 94 mm, 14 g in water) that emits a unique ‘ping’ sequence lasting 3–5 s, with a random silent interval of 20–230 s between sequences. Each decoded transmission is logged by receivers with a timestamp and the shark’s ID code. Transmitters had nominal battery lives of 2–10 years (10-year tags were used on Maui sharks; O ‘ahu sharks had mixed 2–10 year tags), enabling multi-year tracking.We determined receiver detection ranges using a boat-mounted Vemco VR100 hydrophone and test transmitters. We dropped a transmitter from the surface directly above each VR2W receiver, recorded ~ 10 transmissions, then incrementally moved ~ 100 m away (up to 1.5 km) and repeated. By cross-referencing the VR100 GPS log with detections recorded on the stationary VR2W, we identified that VR2W receivers could detect tags at distances up to ~ 900 m.We deployed receivers at twenty-six monitoring sites around Maui (15 sites total, with data recovered from 14) and O ‘ahu (12 sites) (Fig. 2). The array spanned the depth range of the insular shelf, with inshore units deployed at depths of 5 to 20 m and offshore units deployed in deeper waters (100 to 200 m) up to several kilometers offshore. This array design allowed for the comparison of tiger shark presence between deep and shallow areas, between different coasts of the same island, and between Maui and O ‘ahu. Receivers were actively monitoring around Maui from October 2013 until April 2019, and around O ‘ahu throughout and beyond this period. Receivers were deployed on subsurface moorings.Shark capture and taggingShark handling and tagging activities were carried out in accordance with the animal use protocols of the University of Hawai’i at Manoa Institutional Animal Care and Use Committee (IACUC) and were approved under IACUC protocol #05–053. Sharks were captured and tagged around Maui from Oct 2013 to Feb 2015 (26 individuals: 3 M, 23 F) and around O ‘ahu from Apr 2013 to Oct 2018 (16 individuals: 6 M, 10 F). In addition, 17 ‘legacy’ tiger sharks (3 M, 14 F) originally tagged off O ‘ahu prior to this study were still transmitting during all or part of the monitoring period covered by the Maui receiver array. Following the methods of Meyer et al.14, we used demersal longlines baited with large tuna heads, which soaked for 2–4 h at depths of 10–100 m. Targeting these shallower depths typically resulted in a strong female bias in capture rates, as tiger sharks in Hawaiʻi exhibit sexual segregation—with females more commonly occupying nearshore habitats and males more frequently found offshore14. Captured sharks were brought alongside a 6 m skiff, tail-roped, and placed into tonic immobility by inversion. Acoustic transmitters were surgically implanted into the body cavity through a small incision in the abdominal wall, and the incision was closed with interrupted sutures28. Sharks were also tagged with unique external identification tags (Hallprint, Hindmarsh Valley, Australia), then released. The use of internal acoustic transmitters is widespread in shark movement studies and has been shown to have minimal impact on the study subjects29. The size of our acoustic transmitters was small (16 × 94 mm, weight in water 14 g) compared to the size range of the sharks tagged (183–464 cm TL), and surgical implantation procedures were quick and efficient (between 5 and 15 min duration). Our use of tonic immobility as an anesthetic has several advantages, including: rapid induction, minimal disruption to respiration, and immediate and full recovery30. Tiger sharks have been shown to be especially resilient to capture stress. Post-release mortality (PRM) in tiger sharks is very low (0–2% observed31,32,33,34;), and they rank as the least disturbed shark species in terms of capture stress35.Field observationsSharks captured in the field were photo-documented for evidence of recent mating activity, characterized as clasper abrasions or chafing on males and tooth gouges on females.Data analysisMaui receiver site selectionWe used a Gantt chart (Fig. S1) to visualize receiver deployment timelines and identify core sites with the longest continuous monitoring periods and the greatest temporal overlap. Limiting analyses to these core sites enabled us to compare seasonal patterns across the full six years of the study. Of the 14 receiver sites around Maui, six had the most consistent coverage throughout the monitoring period: Kalama Deep, Mākena Pt., Olowalu Shallow, Kalama Shallow, Honokōwai Shallow, and Palauea Shallow (Fig. 2). These sites were selected as the focus for further comparative analyses.Seasonal migration patterns and demography (Rayleigh and F-tests)We conducted a Rayleigh test using the R (v4.4.3; R Core Team 2025) package ‘circular’36 to evaluate whether seasonal migratory patterns differed between sharks captured and tagged around Maui and O ‘ahu. First, we calculated the total observed number of unique individuals from each tagging location (Maui or O ‘ahu) detected around Maui each month. The Rayleigh test identifies departures from uniformity in circular data, where one calendar year is represented as a complete circle. Under the null hypothesis of no seasonal migration, shark detections would be uniformly distributed across months (equal in each month). This test also assumes that any departure from the null hypothesis will be unimodal reflecting a single peak in the distribution. In addition to the Rayleigh test, we calculated the coefficient of variation, variance, and standard deviation to quantify the variability in the number of sharks detected each month for Maui- and O ‘ahu-tagged individuals. These statistics provided insight into the degree of seasonal variation, where high variability in the monthly number of sharks detected may indicate shifts in habitat use and possibly migratory behavior. We used an F-test to compare the variances between the two tagging locations, assessing whether the seasonal variation in the number of sharks detected monthly around Maui differed between Maui and O ‘ahu-tagged individuals. The maturity status of sharks making inter-island movements was determined using the estimated size at first detection, derived from capture size and adjusted based on average annual growth rates for Hawaiian tiger sharks (from37) (Table 1).Table 1 Sex, original tagging date, date of first Maui detection, total length (TL) at tagging, and estimated TL at first Maui detection for sharks originally captured and tagged around O ‘ahu.Full size tableSeasonal comparison using T-test for paired samples, independent T-test, and Rayleigh testMonths were categorized as “Summer” (April through September) or “Winter” (October through March), and monthly numbers of sharks detected at each receiver site were summed separately for each season. Before conducting the t-test, we verified key assumptions. Normality was assessed using the Shapiro–Wilk and Kolmogorov–Smirnov tests, supported by visual inspections of histograms and Q-Q plots38. Independence of observations was confirmed: for the independent t-test, we ensured no correlation between shark detections across sites39, and for the paired t-test, we verified logical pairing of Summer vs. Winter detections within each site40. Equality of variances was tested with Levene’s test41 and outliers were identified using box plots and z-scores42. A paired t-test assessed seasonal differences across all six receiver sites combined, while independent t-tests and Rayleigh tests evaluated seasonal patterns at individual sites. P-values were calculated for each test, and sites were ranked by probability (Tables 2, 3).Table 2 Total unique number, annual mean number (± standard deviation), and p-value of sharks detected during summer and winter at each receiver site.Full size tableTable 3 Rayleigh test of uniformity results for each of the 6 receiver sites, ranked from most to least significant with statistically significant p-values in bold (α = 0.05).Full size tableDiscrete Fourier transformation using fast Fourier transformationTo examine seasonal patterns at the top four ranked receiver sites (Olowalu, Kalama Deep, Kalama Shallow, and Honokōwai), we applied a Discrete Fourier Transformation (DFT) using the Fast Fourier Transformation (FFT) algorithm to time series data representing monthly shark detection counts over the full monitoring period. The DFT converts a time-domain signal into its constituent frequencies, enabling identification of underlying cyclical trends43. The FFT efficiently computes the DFT, allowing rapid analysis of complex temporal signals44. Peaks in the resulting magnitude spectrum indicate dominant frequencies and their corresponding amplitudes, highlighting the strongest periodic patterns in shark detections45.Seasonal trend decomposition using LoessWe used Seasonal Trend Decomposition using Loess (STL) to analyze the time series data of shark detections at Olowalu, the site that showed the most prominent seasonal philopatry. STL is a flexible and robust decomposition method that breaks down time series data into three distinct components: trend, seasonality, and residual46. The trend component reflects the overall direction of the data over time, the seasonality component captures recurring, predictable patterns that occur at fixed intervals (e.g., monthly or yearly), and the residual component represents the random fluctuations or noise that remain after removing the trend and seasonal elements. For our analysis, monthly counts of sharks detected were binned to create the time series data. STL was applied to understand how these counts varied over time, allowing us to distinguish long-term trends and recurring seasonal patterns from random variations.Analysis of diel patterns of shark presence at OlowaluWe used kernel density estimation (KDE)47 to quantify diel overlap in habitat use at Olowalu between male and female tiger sharks. Raw detection data, including detection timestamps, unique transmitter IDs, and sex, were analyzed for the entire monitoring period. To reduce pseudo-replication, we excluded consecutive detections of the same individual at the same receiver within 3 min. From each timestamp, we extracted the hour (0–23) as a numeric column. The kernel density of activity for each sex was estimated in R using the density function, which calculates probability density for activity times and produces a smooth distribution. Both densities were interpolated onto a shared 0–23 h grid and normalized to ensure total probabilities summed to 1 for each sex. Overlap was assessed using the Bhattacharyya Coefficient48, calculated as the sum of square roots of the product of the two densities at each point. This coefficient, ranging from 0 (no overlap) to 1 (perfect overlap), measures distribution similarity. Kernel density estimates were visualized with ggplot249.Median daily root-mean-squared sound pressure levels at Olowalu vs. sharks at OlowaluWe used whale song chorusing data provided by Oceanwide Science Institute’s Ecological Acoustic Recorders (EARs) in the 0.1–1.5 kHz frequency band as a proxy for humpback whale abundance at Olowalu26,27. Median daily root-mean-squared sound pressure levels (RMS SPL) were overlaid with monthly shark detection data at Olowalu to compare the timing of presence and abundance for both species (Fig. 8).To assess time-lagged relationships, we applied a Cross-Correlation Function (CCF) to the monthly maximum RMS SPL and the number of tiger sharks detected per month. This analysis identifies statistically significant correlations and the lag at which they are strongest, revealing whether peaks in shark presence typically precede or follow peaks in acoustic activity.We also conducted a linear regression analysis to directly evaluate the relationship between maximum monthly RMS SPL and monthly tiger shark detections at Olowalu. Model assumptions of normality and homoscedasticity were assessed using residual diagnostic plots. Statistical analyses were performed in R (v4.4.3; R Core Team 2025) using the base lm() function, with significance evaluated at α = 0.05 and model fit assessed via R2 and residual standard error.Land-based humpback whale calf survey data vs. sharks at OlowaluData from land-based visual scan surveys obtained by Kügler et al.27 were used as a proxy for humpback whale calf abundance near Olowalu. Observations were conducted from a cliff site approximately 1 km northwest of Olowalu. Calf counts were normalized by survey effort and overlaid with the monthly time series of tiger shark detections at Olowalu to assess the timing and potential overlap in species presence and abundance.We conducted a linear regression analysis comparing the number of individual tiger sharks detected per month with the average number of whale calves observed per hour, based on multiple daily 30 min scans. Data from 13 months spanning peak whale season (December–April) across three years (2017–2019) were included. Calf observations were normalized to account for variable survey effort. A linear model was fit to test whether monthly variation in tiger shark detections corresponded with changes in calf abundance. Model assumptions of normality and homoscedasticity were assessed using residual diagnostic plots. Statistical analyses were performed in R (v4.4.3; R Core Team 2025) using the base lm() function. Significance was set at α = 0.05, with model fit evaluated using R2 and the residual standard error.We also applied a Cross-Correlation Function (CCF) to the normalized monthly calf averages and tiger sharks detected to assess time-lagged relationships and determine whether peaks in shark presence consistently preceded or followed calf abundance.ResultsOverviewFrom 2013 to 2019, the Maui receiver array detected a total of 44 individual tiger sharks: 8 males (223–408 cm TL) and 36 females (183–464 cm TL). Of these, 21 sharks (48%) had been originally captured and tagged around O ‘ahu (5 of the 8 males and 16 of the 36 females). Detection spans (time between first and last detection on the array) ranged from 1 to 1,990 days (mean = 900 days) for individual sharks, and total detections per shark ranged from 2 to 5,899 (mean = 1,114). Only 5 Maui-tagged tiger sharks were ever detected on the O ‘ahu receiver array, and those detections were sparse (only 3–14 detections each), underscoring the rarity of inter-island movements for Maui-tagged sharks.Broad-scale seasonal movement patternsA comparison of monthly tiger shark detections around Maui revealed significant differences in seasonal patterns between sharks tagged on Maui versus those tagged around O ‘ahu. Sharks tagged around Maui were consistently detected across all months, with no significant seasonal variation in the number of unique individuals detected. In contrast, sharks tagged around O ‘ahu exhibited a clear seasonal cycle, with detections of individuals peaking around Maui in February and reaching their lowest point during the summer months. A Rayleigh test confirmed that detections of Maui-tagged sharks did not deviate significantly from a uniform distribution (R = 0.03, p = 0.71), while O ‘ahu-tagged sharks displayed a significant peak, indicating a non-uniform distribution and demonstrating their seasonal presence around Maui (R = 0.28, p = 0.006) (Fig. 3). Additionally, the coefficient of variation for O ‘ahu-tagged sharks was 49.5% compared to 5.7% for Maui-tagged sharks, indicating much higher variability in O ‘ahu sharks’ detection patterns. The variance of O ‘ahu-tagged sharks detected around Maui was 6.9, reflecting a greater spread from the mean, whereas Maui-tagged sharks had a variance of 1.5. The F-test confirmed a significant difference between the variances of the two groups (F(11,11) = 4.5, p = 0.01). Out of the 21 O ‘ahu-tagged sharks that visited Maui, 14 (67%) were later detected back at O ‘ahu at least once. The maximum number of roundtrips observed for any individual shark between O ‘ahu and Maui was four (Fig. S2). Seven O ‘ahu-tagged sharks were not detected anywhere following their detections around Maui; however, most had previously been detected around O ‘ahu before appearing around Maui. Eight O ‘ahu-tagged individuals (36%) were detected in Maui waters during the tiger shark mating season months (January–February), but only one of those appeared in multiple mating seasons.Fig. 3Total numbers of sharks detected per month on Maui receivers for all years combined. Maui-tagged sharks: sharks originally captured and tagged around Maui. O ‘ahu-tagged sharks: sharks originally captured and tagged around O ‘ahu.Full size imageDemographic patterns of inter-island movementsOf the 21 tiger sharks (16 females and 5 males) captured, tagged in O ‘ahu waters, and later detected around Maui at any time of year, 17 (80%) were sexually mature at the time of their first detection in Maui waters (Table 1). Six individuals were sexually immature when tagged and only detected around Maui after they reached sexual maturity (lengths at detection estimated using tiger shark growth curve from37 and maturity status at detection estimated from maturity data in13), 4 were sexually immature when tagged and still sexually immature when detected, and 11 were sexually mature when initially tagged. Among the 13 O ‘ahu individuals (12 females and 1 male) detected at any Maui receiver site during the peak mating season months of January and February 11 were sexually mature.Evidence for seasonal aggregations at specific Maui locationsThe total number of individuals detected seasonally at each of the 6 core Maui monitoring sites ranged from 8 (Honokowai, summer) to 32 (Kalama Deep, winter) (Table 2). The overall mean number of sharks detected at these sites during winter (25.5 ± 5.68) was significantly higher than during summer (20 ± 6.81) (paired t-test, t = − 4.68, df = 5, p = 0.015). A t-test for independent samples comparing summer and winter means at each site found that all six sites exhibited significantly higher mean shark counts during winter than summer months. However, the level of significance for these seasonal differences varied across sites (Table 2).Aggregate seasonal histograms showing the number of individuals detected in each calendar month across the entire 6 year monitoring period indicate that the seasonal pattern is more clearly defined at Olowalu than at any other site (Fig. 4). Rayleigh tests performed on each individual site confirmed Olowalu as having the most significant peak (Table 3).Fig. 4Aggregate monthly detections of individual sharks at each of the six receiver sites.Full size imageDiscrete Fourier Transforms (DFTs) performed on the four receiver sites with significant p-values revealed a clear peak in amplitude density at a 1-year (annual) frequency for Olowalu (Fig. 5). This dominant peak indicates that annual cycles are the strongest temporal pattern in the Olowalu time series of tiger shark detections. Kalama Deep showed a similar, though slightly weaker, annual peak, suggesting a comparable cyclical trend. In contrast, Kalama Shallow and Honokōwai exhibited only low-amplitude peaks, indicating a lack of strong or consistent seasonal patterns in shark detections at those sites.Fig. 5Fast Fourier Transformations (FFTs) for the 4 significant Rayleigh test sites. Left panel shows detrended time series for each receiver site, right panel shows the dominant frequency extracted from each time series.Full size imageSeasonal Trend Decomposition using Loess also identified a strong cyclical seasonal pattern of shark detections at Olowalu, combined with a long-term trend showing an initial rise in shark detections during the early tagging phase, followed by a gradual decline over the later years (Fig. 6). The remainder was confirmed to be residual noise using Shapiro–Wilk normality test and examination of QQ plot.Fig. 6Seasonal trend decomposition using Loess for sharks detected at Olowalu. Panels from top to bottom show the original time-series data of shark detections (Data – number of individuals detected), the long-term underlying trend indicating an initial increase during the shark tagging phase followed by a gradual decline (Trend), the seasonal component highlighting consistent cyclical variation in shark presence after removing the overall trend (Seasonal), and the residual variability (Remainder).Full size imageDiel activity patternsA kernel density plot (Fig. 7) revealed substantial temporal overlap between sexes at Olowalu. The Bhattacharyya coefficient of 0.983 for the diel activity patterns of males and females confirmed this overlap. Both sexes were more consistently present during the day than at night, with overlapping peaks in presence at approximately 1500 h. In addition, multiple sharks captured at this site had physical signs of recent mating activity (females with fresh mating scars and males with visibly chafed claspers (Figs. 8, 9)).Fig. 7Kernel density plot of activity by sex for male and female sharks detected at Olowalu.Full size imageFig. 8Male tiger shark captured at Olowalu, Maui during the known tiger shark mating season in Hawai’i. View the distinct abrasions on his right clasper.Full size imageFig. 9Multiple female tiger sharks captured at Olowalu, Maui during the known tiger shark mating season in Hawai’i. Tooth gouges can be seen on their dorsal fins, head, gills, and caudal fin.Full size imageSex, size and maturity status of sharks detected at Olowalu, MauiAmong the O ‘ahu-tagged individuals (8 females and 0 males) detected at Olowalu during the peak tiger shark mating season months of January and February, 7 (87.5%) were sexually mature. Outside of mating season, there were 7 O ‘ahu-tagged tiger sharks (6 females and 1 male) detected at Olowalu, 5 of which were sexually mature.Comparison of tiger shark detection patterns with humpback whale song intensityDaily RMS SPL values (used as a proxy for humpback whale presence) plotted against monthly shark detections at Olowalu revealed consistent but slightly offset peaks in abundance for each species (Fig. 10). Cross-correlation analysis confirmed this offset, indicating a one-month time lag in which peak tiger shark detections preceded peak whale call intensity (best lag = 1 month, r = 0.821; Fig. 11). Linear regression analysis showed a significant positive relationship between the number of tiger sharks detected per month and the monthly maximum RMS SPL (β = 0.387, SE = 0.059, t = 6.511, p < 0.001). Residual diagnostics indicated no clear violations of model assumptions, suggesting a good overall fit.Fig. 10Daily root mean square sound pressure levels (RMS SPL) in dB (black dots) recorded off Olowalu vs monthly acoustically tagged sharks (solid blue line) detected at Olowalu.Full size imageFig. 11Cross-correlation function for monthly maximum RMS SPL vs. the number of sharks detected per month at Olowalu. Dashed blue lines represent significance and solid black lines represent time lags.Full size imageComparison of tiger shark detection patterns with whale calf survey dataNormalized monthly averages of humpback whale calf counts plotted against monthly individual tiger shark detections at Olowalu show closely aligned peaks across the 13 months of available data (Fig. 12). Cross-correlation analysis confirmed this synchrony, indicating no time lag between the two patterns (best lag = 0 months, r = 0.749; Fig. 13). Linear regression analysis revealed a significant positive relationship between monthly tiger shark detections and average whale calf counts from shore-based surveys (p = 0.00316). The model explained 56.23% of the variance in shark presence (R2 = 0.5623, Adjusted R2 = 0.5225), suggesting a moderate association between the two variables. However, a residual standard error of 2.272 indicates that additional unmeasured factors likely influence tiger shark presence during peak winter months.Fig. 12Normalized monthly average of humpback whale calves per month (red) vs. monthly individual sharks detected (black) at Olowalu during three different whale seasons.Full size imageFig. 13Cross-correlation function for monthly average humpback whale calves vs. the number of sharks detected per month at Olowalu. Blue dashed lines represent significance; solid black lines represent time lags.Full size imageDiscussionUnderstanding the ecological drivers shaping apex predator distributions is essential for predicting species interactions, identifying important habitats, and informing effective marine conservation strategies4,50,51. Here, we combined long-term acoustic telemetry with demographic analyses to investigate the seasonal site-specific presence of tiger sharks in waters around Maui (Hawaiian Islands). Our findings suggest that the seasonal aggregation of tiger sharks around Maui, particularly at Olowalu, is consistent with a combination of reproductive activities and opportunistic foraging on whale associated biomass. Four main lines of evidence support this interpretation: (1) Seasonal inter-island migrations to Maui that coincide with the known tiger shark mating period (mid-winter) and overlap with humpback whale calving season; (2) Demographic patterns indicating migrating sharks are predominantly sexually mature (80% mature at first Maui detection) which is consistent with mating driven movement; (3) Spatially and temporally overlapping occurrences of mature males and females at Olowalu during mid-winter, together with independent evidence of recent mating (fresh mating scars on females and clasper chafing on males; Figs. 8 and 9), provide circumstantial support for potential mating interactions at this site; and (4) A temporal alignment between shark presence and peak whale calf abundance, implying that foraging opportunities (e.g., scavenging whale placentas or carcasses) may also influence shark aggregations.Seasonal inter-island movements indicating reproductive migrationsTiger sharks tagged around O ‘ahu showed distinct seasonal peaks near Maui, especially in January and February (mating season), whereas sharks tagged around Maui displayed year-round residency. Most O ‘ahu-tagged sharks returned to O ‘ahu after visiting Maui. Given the three-year gestation period described by Whitney and Crow13, successfully mated females would not be expected to revisit mating grounds for at least three years, allowing time to gestate, give birth, and recover. Thus, detection of adult females at suspected mating grounds in consecutive years would contradict the mating migration hypothesis. We observed only one instance of an adult female returning during mating season in back-to-back years (Fig. S3). All other sharks were detected during only one mating season (Fig. S3). Taken together, these observations indicate directed, seasonal partial migrations by O’ahu-tagged tiger sharks that coincide with Hawai ‘i’s mid-winter mating period13. This suggests reproduction as a driver for these seasonal migrations; the overlap of which peaks during whale calving events27.Partial migration describes the behavior of populations composed of individuals with varying degrees of site attachment due to factors such as reproductive status, local competition, predation risk, and body condition52. The contrasting patterns observed between O’ahu-tagged and Maui-resident sharks may reflect differences in the physical and ecological settings of each island. O’ahu and Maui differ in oceanography, bathymetry, coastal habitat structure, and levels of human activity, all of which could influence shark residency and movement. Maui’s extensive insular shelf and proximity to whale calving grounds may favor year-round occupancy, whereas O’ahu’s more developed coastline and narrower shelf may limit suitable habitats for tiger sharks, encouraging seasonal migration. There is evidence that some tiger shark migrations are driven by reproduction. In Hawai ‘i, mature females from the Northwestern Hawaiian Islands migrate to the Main Hawaiian Islands during the fall pupping season, highlighting parturition as a key migratory driver53. Similarly, in the northwest Atlantic, mature male tiger sharks migrate from open-ocean habitats to specific reef areas for the mating season, implicating mating as the primary driver54. Comparable reproduction-driven partial migrations occur in other shark species, including lemon sharks55, in which only a subset of the population migrates to distinct breeding locations.The observed seasonal influx of sharks from O ‘ahu combined with the high residency of Maui sharks suggests a spatially structured mating system. Sharks with core habitats located outside Maui Nui appear to specifically migrate to this region for mating opportunities, whereas local sharks remain resident year-round. However, given that Olowalu is also a known hotspot for whale calves and placental resources56,57, this dual timing and location may not be coincidental. Both mating and foraging may jointly influence tiger shark seasonal movements to Maui. Access to calorie-dense whale blubber during the breeding season could substantially improve female energetic condition, as large sharks readily scavenge whale carcasses and preferentially consume lipid-rich blubber58. Fecundity in many sharks scales with female body size (a proxy for energetic condition59;), and therefore access to high-calorie prey pulses (e.g. fledgling seabirds at French Frigate Shoals; migratory birds along the Gulf coast; or scavenged whale blubber) can subsidize females’ energy budgets and help meet the substantial costs of viviparous reproduction5,58,60.Demographic evidence supports mating hypothesisExtensive tagging and long-term monitoring, coupled with established tiger shark growth rates in Hawai ‘i37, allowed us to estimate size at first detection on Maui for several O ‘ahu-tagged individuals. We found that 80% of O ‘ahu-tagged sharks detected around Maui were already sexually mature at their initial detection. Notably, several sharks initially tagged as juveniles only appeared in Maui waters after reaching estimated maturity. Similar maturity-dependent migratory behaviors have been documented in tiger sharks from the northwest Atlantic, suggesting that these migrations are reproductive in nature54. Such ontogenetic shifts in habitat use and behavior are widespread among elasmobranchs61 and typically represent transitions from juvenile priorities, such as foraging or predation avoidance, to adult reproductive strategies. However, these patterns do not preclude additional drivers. Not all sharks arriving at Maui were mature, and the presence of some juvenile sharks suggest that factors like foraging could also play a role.Seasonal aggregation and diel synchrony at OlowaluAmong the six Maui shelf monitoring sites, Olowalu exhibited the strongest and most consistent seasonal pattern of tiger shark detections. Diel activity at Olowalu revealed near-complete overlap (98.3% overlap by kernel density) between male and female presence, possibly indicating synchronized habitat use during daytime that may facilitate mating interactions. This aligns with the current operational definition for aggregation in elasmobranch species, characterized by the co-occurrence of two or more individuals in space and time due to the deliberate use of a common driver62. Although males appeared underrepresented in our detections, this may reflect a sampling bias stemming from difficulties capturing mature males in nearshore habitats14, rather than their actual absence. The fresh mating scars observed on females and chafed claspers on males provide physical evidence of active mating at this site, similar to observations that have supported Fernando de Noronha as a reproductive area for tiger sharks in the South Atlantic63.Understanding the mating systems of tiger sharks is inherently challenging due to their large size, mobility, and generally solitary nature64. Our findings align with theoretical models proposing that even low-density aggregations can substantially enhance reproductive success in wide-ranging solitary species by increasing encounter rates among receptive individuals65,66. Rather than forming dense clusters, tiger sharks may form diffuse aggregations spanning several kilometers over extended periods. This coordinated yet dispersed aggregation at Olowalu appears to be a functionally significant reproductive strategy that balances mating opportunities against ecological constraints such as the energetic costs of migration, intra-specific competition, and the potential unpredictability of whale-derived food resources66,67. Such strategies are especially advantageous for sparsely distributed marine predators, reflecting an adaptive compromise between solitary lifestyles and reproductive needs.Correlations with whale biomass indicate trophic opportunitiesComparing the spatial and temporal patterns of predators and prey enables researchers to assess the likelihood of interactions between species68. To evaluate the whale biomass foraging hypothesis, we examined associations between tiger shark presence and proxies of humpback whale biomass—specifically adult humpback whale song chorusing intensity and calf counts. Our analysis revealed a positive relationship between monthly tiger shark abundance and humpback whale acoustic activity, predominantly reflecting adult male singing. However, peak shark abundance occurred one month before peak adult whale acoustic activity. There are multiple potential explanations for this phenomenon, namely (1) adult whales are unlikely to be the primary factor attracting sharks, (2) sharks may position themselves early to secure access to predictable resources, or (3) both sharks and whales may simply be responding to shared environmental cues (e.g. ocean temperature). Further fine-scale monitoring will be required to disentangle anticipatory behavior from coincidental timing. Conversely, tiger shark abundance closely aligned with peak calf numbers, suggesting calves, placentas, or stillborn and vulnerable neonates may provide important, low-risk foraging opportunities. The moderate explanatory power (R2 = 0.56) of whale biomass on shark abundance, observed across the 13 months when whale calf data were available within the broader six-year monitoring dataset, is noteworthy for ecological studies69. This relationship suggests that whale-derived nutrients may indeed influence shark aggregation, although coincidental timing driven by shared migratory cues again cannot be ruled out. Tiger sharks are known opportunistic scavengers of whale carcasses7 and potentially consume placental or neonatal tissues. The predictable seasonal presence of whale-derived resources off Olowalu aligns well with observed shark aggregations. Similar seasonal foraging-driven shark aggregations have been documented elsewhere. One example is at French Frigate Shoals Atoll (Kānemiloha ‘i) in the Northwest Hawaiian Islands where tiger sharks aggregate in early summer specifically to prey upon fledgling albatross chicks, with shark presence closely matching the narrow seasonal and diel timing of fledgling events, primarily between sunrise and noon5. Such precise foraging-driven aggregations may be relatively rare within the broader context of tiger shark long-term movement patterns. For example, tiger sharks showed low overall site fidelity and no increase in fidelity over time at an ecotourism provisioning site70; individual prey species occurrence patterns did not explain tiger shark residency patterns in the northern Great Barrier Reef71; tiger shark proximity to a turtle nesting island remained consistent between nesting and non-nesting seasons68; and, although tiger sharks preferred shallow habitats where prey was abundant in Australia, prey availability did not explain their broader-scale movements72.Given Olowalu’s role as a hotspot for whale-calf pairs56,57,73 tiger shark reproductive activities likely coincide with significant foraging opportunities provided by nutrient-rich whale-derived resources. Our findings collectively suggest that tiger shark aggregations around Olowalu are influenced by both reproductive strategies and seasonal availability of whale biomass.Ecological significance and future studiesExplicit identification of mating aggregations in elasmobranchs remains uncommon, with only a few documented cases, such as nurse sharks (Ginglymostoma cirratum74;), Port Jackson sharks (Heterodontus portusjacksoni75;), and potentially white sharks (Carcharodon carcharias) at Guadalupe Island76. Most studies, however, infer mating aggregations indirectly from observed spatial and temporal patterns77,78. Beyond identifying mating aggregations, it is also important to consider the ecological attributes that define breeding and nursery areas. Shark breeding and/or nursery sites may reflect a combination of predictable prey availability, benthos type, depth, and predation risk66. The year-round residency for Maui-tagged sharks may therefore reflect a convergence of both functions, offering reproductive opportunities and reliable access to food resources that make the region suitable for multiple life-history stages.The convergence of mature tiger sharks during a defined seasonal window, their pronounced site fidelity to Olowalu—including repeated returns by specific individuals over seven years—and clear diel synchrony between sexes collectively suggest that Olowalu serves as a reproductive site for tiger sharks in Hawai ‘i. Fidelity to mating areas has been documented in only a few shark species66; notably, nurse sharks exhibit strong long-term fidelity, returning annually to the Dry Tortugas mating site over periods spanning up to 16 mating seasons and nearly three decades79. Similarly, our findings suggest mating-site fidelity among tiger sharks at Olowalu. Future research should adopt multi-modal approaches, such as biologging tags with video capabilities to directly quantify conspecific interactions, verify mating events, and document shark-whale interactions14. Other promising approaches include cloacal swabbing to detect whale DNA to assess the importance of scavenging events80 and energetic modeling to evaluate the relative importance of whale-derived nutrients.ConclusionThe temporal overlap between tiger shark aggregation and peak whale-calf biomass suggests that Olowalu aggregations may serve dual roles—supporting both reproductive and foraging activities. As generalist and opportunistic predators, tiger sharks can readily exploit these whale-derived resources while concurrently engaging in mating behaviors. Our integrative analysis of movement patterns, demographic structure, diel behavior, and seasonal occurrence provides the first evidence of seasonal mating aggregations for tiger sharks and advances our understanding of their mating behavior in Hawai’i.
Data availability
The data and accompanying code are hosted on Zenodo and will be made publicly available upon publication. A private access link has been provided for peer review: https://doi.org/10.5281/zenodo.15558374.
ReferencesCompagno, L. J. V. FAO species catalogue. Volume 4. Sharks of the world. An annotated and illustrated catalogue of shark species known to date. Part 2. Carcharhiniformes. FAO Species Catalogue 4(2), 251–655 (1984).
Google Scholar
Ferreira, L. C. et al. The trophic role of a large marine predator, the tiger shark Galeocerdo cuvier. Sci. Rep. 7(1), https://doi.org/10.1038/s41598-017-07751-2 (2017).Holland, K. N. et al. A perspective on future tiger shark research. Front. Mar. Sci. 6, 37. https://doi.org/10.3389/fmars.2019.00037 (2019).Article
Google Scholar
Heithaus, M. R., Frid, A., Wirsing, A. J. & Worm, B. Predicting ecological consequences of marine top predator declines (Elsevier Ltd., 2008).Book
Google Scholar
Meyer, C. G., Papastamatiou, Y. P. & Holland, K. N. A multiple instrument approach to quantifying the movement patterns and habitat use of tiger (Galeocerdo cuvier) and Galapagos sharks (Carcharhinus galapagensis) at French Frigate Shoals, Hawaii. Mar. Biol. 157(8), 1857–1868. https://doi.org/10.1007/s00227-010-1457-x (2010).Article
Google Scholar
Vossgaetter, L. et al. Non-invasive methods characterise the world’s largest tiger shark aggregation in Fuvahmulah, Maldives. Sci. Rep. 14(1), 21998. https://doi.org/10.1038/s41598-024-73079-3 (2024).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Clua, E., Chauvet, C., Read, T., Werry, J. M. & Lee, S. Y. Behavioural patterns of a tiger shark (Galeocerdo cuvier) feeding aggregation at a blue whale carcass in Prony Bay, New Caledonia. Mar. Freshw. Behav. Physiol. 46(1), 1–20. https://doi.org/10.1080/10236244.2013.773127 (2013).Article
Google Scholar
Jacoby, D. M. P. et al. Social network analysis reveals the subtle impacts of tourist provisioning on the social behavior of a generalist Marine Apex Predator. Front. Mar. Sci. 8, 665726. https://doi.org/10.3389/fmars.2021.665726 (2021).Article
Google Scholar
Hammerschlag, N., Gutowsky, L. F. G., Gallagher, A. J., Matich, P. & Cooke, S. J. Diel habitat use patterns of a marine apex predator (tiger shark, Galeocerdo cuvier) at a high use area exposed to dive tourism. J. Exp. Mar. Biol. Ecol. 495, 24–34. https://doi.org/10.1016/j.jembe.2017.05.010 (2017).Article
Google Scholar
Sulikowski, J. A. et al. Identification of the first gestational ground for tiger sharks (Galeocerdo cuvier) in the Central Indian Ocean using a high-definition submersible ultrasound. Front. Mar. Sci. 11, 1500176. https://doi.org/10.3389/fmars.2024.1500176 (2024).Article
Google Scholar
Reinero, F. R. et al. First insights into social behavioral patterns between pairs of bait-attracted mature female tiger sharks from Fuvahmulah Island, Maldives. Behav. Proc. 229, 105216. https://doi.org/10.1016/j.beproc.2025.105216 (2025).Article
Google Scholar
Shields, C., Reproductive biology of the tiger shark in the Western Atlantic reproductive biology of the tiger shark in the Western Atlantic Ocean Ocean, (2018).Whitney, N. M. & Crow, G. L. Reproductive biology of the tiger shark (Galeocerdo cuvier) in Hawaii. Mar. Biol. 151(1), 63–70. https://doi.org/10.1007/s00227-006-0476-0 (2007).Article
Google Scholar
Meyer, C. G. et al. Habitat geography around Hawaii’s oceanic islands influences tiger shark (Galeocerdo cuvier) spatial behaviour and shark bite risk at ocean recreation sites. Sci. Rep. 8(1), 4945. https://doi.org/10.1038/s41598-018-23006-0 (2018).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Salinas-De-León, P. et al. A matter of taste: Spatial and ontogenetic variations on the trophic ecology of the tiger shark at the Galapagos marine reserve. PLoS ONE 14(9), e0222754. https://doi.org/10.1371/journal.pone.0222754 (2019).Article
CAS
PubMed
PubMed Central
Google Scholar
Helweg, D. A., Daily and Seasonal patterns of behavior and Abundance of Humpback Whales (Megaptera novaeangliae) in Hawaiian Waters, University of Hawaii at Manoa, (1989).Tucker, J. P., Vercoe, B., Santos, I. R., Dujmovic, M. & Butcher, P. A. Whale carcass scavenging by sharks. Glob Ecol. Conserv. 19, e00655. https://doi.org/10.1016/j.gecco.2019.e00655 (2019).Article
Google Scholar
Gallagher, A. J., Papastamatiou, Y. P. & Barnett, A. Apex predatory sharks and crocodiles simultaneously scavenge a whale carcass. J Ethol 36(2), 205–209. https://doi.org/10.1007/s10164-018-0543-2 (2018).Article
Google Scholar
Dicken, M. L. et al. Diet and trophic ecology of the tiger shark (Galeocerdo cuvier) from South African waters. PLoS ONE 12(6), e0177897. https://doi.org/10.1371/journal.pone.0177897 (2017).Article
CAS
PubMed
PubMed Central
Google Scholar
Fletcher, C. H. et al. Geology of Hawaii Reefs. In Coral Reefs of the USA, Springer Netherlands, pp. 435–487. https://doi.org/10.1007/978-1-4020-6847-8_11 (2008).Jokiel, P. L. Biology and ecological functioning of Coral Reefs in the Main Hawaiian Islands. In Coral Reefs of the USA, Springer Netherlands, pp. 489–517. https://doi.org/10.1007/978-1-4020-6847-8_12 (2008).Brown, D. An ecological comparison of turf algae between two sites on West Maui that differ in anthropogenic impacts,” University of Hawaii at Manoa, (2019).Brown, E. K. Reef Coral populations: Spatial and temporal differences observed on six Reefs Off West Maui,” University of Hawaii at Manoa, (2004).Wei, J. et al. Shallow water bathymetry with multi-spectral satellite ocean color sensors: Leveraging temporal variation in image data. Remote Sens. Environ. 250, 112035. https://doi.org/10.1016/j.rse.2020.112035 (2020).Article
Google Scholar
Salden, D. R. Humpback Whale encounter rates Offshore of Maui, Hawaii, (1988).Kugler, A., Lammers, M. O., Zang, E. J., Kaplan, M. B. & Aran Mooney, T. Fluctuations in Hawaii’S Humpback Whale Megaptera Novaeangliae population inferred from male song Chorusing Off Maui. Endanger Species Res 43, 421–434. https://doi.org/10.3354/ESR01080 (2020).Article
Google Scholar
Kügler, A., Lammers, M. O., Zang, E. J., Pack, A. A., Male Humpback Whale Chorusing in Hawai‘i and its Relationship with Whale abundance and density. Front Mar Sci, 8, https://doi.org/10.3389/fmars.2021.735664 (2021).Holland, K. N., Wetherbee, B. M., Lowe, C. G. & Meyer, C. G. Movements of tiger sharks (Galeocerdo cuvier ) in coastal Hawaiian waters. Mar Biol 134, 665–673. https://doi.org/10.1007/s002270050582 (1999).Article
Google Scholar
Heim, V., van Zinnicq Bergmann, M. P. M., Smukall, M. J. & Guttridge, T. L. Multiyear tourism-related feeding reduces short- and long-term local space use in a marine apex predator. Anim. Behav. 217, 81–107. https://doi.org/10.1016/j.anbehav.2024.08.012 (2024).Article
Google Scholar
Kessel, S. T. & Hussey, N. E. Tonic immobility as an anaesthetic for elasmobranchs during surgical implantation procedures. Can. J. Fish. Aquat. Sci. 72(9), 1287–1291. https://doi.org/10.1139/cjfas-2015-0136 (2015).Article
Google Scholar
Afonso, A. S. & Hazin, F. H. V. Post-release survival and behavior and exposure to fisheries in juvenile tiger sharks, Galeocerdo cuvier, from the South Atlantic. J. Exp. Mar. Biol. Ecol. 454, 55–62. https://doi.org/10.1016/j.jembe.2014.02.008 (2014).Article
Google Scholar
Binstock, A. L. et al. Variable post-release mortality in common shark species captured in Texas shore-based recreational fisheries. PLoS ONE 18(2), e0281441. https://doi.org/10.1371/journal.pone.0281441 (2023).Article
CAS
PubMed
PubMed Central
Google Scholar
Grosse, T. A. Assessing survival rates of discarded sandbar (Carcharhinus plumbeus), tiger sharks (Galeocerdo cuvier), Port Jackson sharks (Heterodontus portusjacksoni) and dusky sharks (Carcharhinus obscurus),” Curtin University, (2023).Whitney, N. M. et al. Connecting post-release mortality to the physiological stress response of large coastal sharks in a commercial longline fishery. PLoS ONE 16(9), e0255673. https://doi.org/10.1371/journal.pone.0255673 (2021).Article
CAS
PubMed
PubMed Central
Google Scholar
Gallagher, A. J., Serafy, J. E., Cooke, S. J. & Hammerschlag, N. Physiological stress response, reflex impairment, and survival of five sympatric shark species following experimental capture and release. Mar Ecol Prog Ser 496, 207–218. https://doi.org/10.3354/meps10490 (2014).Article
ADS
Google Scholar
Lund, U., Agostinelli, C. Package ‘circular,’” 2017, Repository CRAN 775.5. [Online]. Available: https://orcid.org/0000-0001-6702-4312Meyer, C. G. et al. Growth and maximum size of tiger sharks (Galeocerdo cuvier) in Hawaii. PLoS ONE 9(1), e84799. https://doi.org/10.1371/journal.pone.0084799 (2014).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Shapiro, S. S., Wilk, M. B. An analysis of variance test for normality (complete samples),” Biometrika, vol. 52, no. 3–4, pp. 591–611, 1965, [Online]. Available: https://academic.oup.com/biomet/article/52/3-4/591/336553Field, A. Discovering statistics using IBM SPSS statistics. Sage publications limited, (2013).Hurlbert, S. H. Pseudoreplication and the design of ecological field experiments. Ecol. Monogr. 54(2), 187–211. https://doi.org/10.2307/1942661 (1984).Article
Google Scholar
Levene, H., Robust tests for equality of variances,” (1960).Tukey, J. W., Exploratory data analysis, Reading/Addison-Wesley, (1977).Bracewell, R. N., The fourier transform and its applications, 3rd ed. McGraw-Hill Science/Engineering/Math, (1999).Cooley, J. W., Tukey, J. W. An algorithm for the machine calculation of complex fourier series, 1965. [Online]. Available: https://www.jstor.org/stable/2003354?seq=1&cid=pdf-Oppenheimer, A., Schafer, R. Discrete-time signal processing, 3rd ed. Pearson, (2009).Cleveland, R. B., Cleveland, W. S., McRae, J. E. & Terpenning, I. STL: A seasonal-trend decomposition procedure based on Loess. J. Off. Stat. 6(1), 3–73 (1990).
Google Scholar
Ridout, M. S. & Linkie, M. Estimating overlap of daily activity patterns from camera trap data. J. Agric. Biol. Environ. Stat. 14(3), 322–337. https://doi.org/10.1198/jabes.2009.08038 (2009).Article
MathSciNet
Google Scholar
Bhattacharyya, A. On a measure of divergence between two statistical populations defined by their probability distribution. Bull. Calcutta. Math. Soc. 35, 99–110 (1943).MathSciNet
Google Scholar
Wickham, H. et al. ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics, The R Foundation. https://doi.org/10.32614/CRAN.package.ggplot2. (2007).Block, B. A. et al. Tracking apex marine predator movements in a dynamic ocean. Nature 475(7354), 86–90. https://doi.org/10.1038/nature10082 (2011).Article
CAS
PubMed
Google Scholar
Estes, J. A. et al., Trophic downgrading of planet Earth,” 2011. [Online]. Available: https://www.science.orgChapman, B. B., Brönmark, C., Nilsson, J. Å. & Hansson, L. A. The ecology and evolution of partial migration. Oikos 120(12), 1764–1775. https://doi.org/10.1111/j.1600-0706.2011.20131.x (2011).Article
ADS
Google Scholar
Papastamatiou Y. P., Meyer, C. G., Carvalho, F., Dale, J. J., Hutchinson, M. R., Holland, K. N. Telemetry and random-walk models reveal complex patterns of partial migration in a, (2013).Lea, J. S. E. et al. Repeated, long-distance migrations by a philopatric predator targeting highly contrasting ecosystems. Sci. Rep. 5, 11202. https://doi.org/10.1038/srep11202 (2015).Article
ADS
PubMed
PubMed Central
Google Scholar
Pillans, R. D. et al. Long-term acoustic monitoring reveals site fidelity, reproductive migrations, and sex specific differences in habitat use and migratory timing in a large Coastal shark (Negaprion acutidens). Front. Mar. Sci. 8, 616633. https://doi.org/10.3389/fmars.2021.616633 (2021).Article
Google Scholar
Cartwright, R. et al. Between a rock and a hard place: Habitat selection in female-calf humpback whale (megaptera novaeangliae) pairs on the hawaiian breeding grounds. PLoS ONE 7(5), e38004. https://doi.org/10.1371/journal.pone.0038004 (2012).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Pack, A. A. et al. Comparing depth and seabed terrain preferences of individually identified female humpback whales (Megaptera novaeangliae), with and without calf, off Maui, Hawaii. Mar. Mamm Sci. 34(4), 1097–1110. https://doi.org/10.1111/mms.12495 (2018).Article
Google Scholar
Fallows, C., Gallagher, A. J. & Hammerschlag, N. White sharks (Carcharodon carcharias) Scavenging on Whales and its potential role in further shaping the ecology of an apex predator. PLoS ONE 8(4), e60797. https://doi.org/10.1371/journal.pone.0060797 (2013).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Cortés, E. Life history patterns and correlations in sharks. Rev. Fish. Sci. 8(4), 299–344. https://doi.org/10.1080/10408340308951115 (2000).Article
Google Scholar
Drymon, J. M. et al. Tiger sharks eat songbirds: scavenging a windfall of nutrients from the sky. Ecology 100(9), 1–4. https://doi.org/10.1002/ecy.2728 (2019).Article
Google Scholar
Grubbs, R. D., 7 Ontogenetic shifts in movements and Habitat Use.McInturf, A. G. A. et al. A unified paradigm for defining elasmobranch aggregations. ICES J. Mar. Sci. 80(6), 1551–1566. https://doi.org/10.1093/icesjms/fsad099 (2023).Article
Google Scholar
Rangel, B. S. et al. Evidence of mating scars in female tiger sharks (Galeocerdo cuvier) at the Fernando de Noronha Archipelago, Brazilian Equatorial Atlantic. Environ. Biol. Fishes 106(1), 107–115. https://doi.org/10.1007/s10641-022-01380-z (2023).Article
Google Scholar
Sulikowski, J. A. et al. Seasonal and life-stage variation in the reproductive ecology of a marine apex predator, the tiger shark Galeocerdo cuvier, at a protected female-dominated site. Aquat Biol 24(3), 175–184. https://doi.org/10.3354/ab00648 (2016).Article
Google Scholar
Kokko, H. Rankin, D. J. Lonely hearts or sex in the city? Density-dependent effects in mating systems. In Philosophical transactions of the royal society B: Biological sciences, Royal society, pp. 319–334. https://doi.org/10.1098/rstb.2005.1784 (2006).Speed, C. W., Field, I. C. Meekan, M. G., Bradshaw, C. J. A. Complexities of coastal shark movements and their implications for management, https://doi.org/10.3354/meps08581 (2010).Chapman, D. D., Feldheim, K. A., Papastamatiou, Y. P. & Hueter, R. E. There and back again: A review of residency and return migrations in sharks, with implications for population structure and management. Ann Rev Mar Sci 7, 547–570. https://doi.org/10.1146/annurev-marine-010814-015730 (2015).Article
PubMed
Google Scholar
Fitzpatrick, R. et al. A comparison of the seasonal movements of tiger sharks and green turtles provides insight into their predator-prey relationship. PLoS ONE 7(12), e51927. https://doi.org/10.1371/journal.pone.0051927 (2012).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Low-Décarie, E., Chivers, C. & Granados, M. Rising complexity and falling explanatory power in ecology. Front Ecol Environ 12(7), 412–418. https://doi.org/10.1890/130230 (2014).Article
Google Scholar
Séguigne, C., Bègue, M., Meyer, C., Mourier, J. & Clua, É. Provisioning ecotourism does not increase tiger shark site fidelity. Sci. Rep. 13(1), 7785. https://doi.org/10.1038/s41598-023-34446-8 (2023).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Werry, J. M. et al. Reef-fidelity and migration of tiger sharks, Galeocerdo cuvier, across the coral sea. PLoS ONE 9(1), e83249. https://doi.org/10.1371/journal.pone.0083249 (2014).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Heithaus, M. R., Wirsing, A. J., Dill, L. M. & Heithaus, L. I. Long-term movements of tiger sharks satellite-tagged in Shark Bay, Western Australia. Mar Biol 151(4), 1455–1461. https://doi.org/10.1007/s00227-006-0583-y (2007).Article
Google Scholar
Kugler, A. Male humpback whale chorusing and what it reveals about the species’ ecology in Hawaiʻi,” University of Hawaii at Manoa, (2022).Whitney, N. M., Pratt, H. L. & Carrier, J. C. Group courtship, mating behaviour and siphon sac function in the whitetip reef shark, Triaenodon obesus. Anim Behav 68(6), 1435–1442. https://doi.org/10.1016/j.anbehav.2004.02.018 (2004).Article
Google Scholar
Mourier, J., Bass, N. C., Guttridge, T. L., Day, J. & Brown, C. Does detection range matter for inferring social networks in a benthic shark using acoustic telemetry?. R Soc Open Sci 4(9), 170485. https://doi.org/10.1098/rsos.170485 (2017).Article
ADS
PubMed
PubMed Central
Google Scholar
Domeier, M. L. & Nasby-Lucas, N. Two-year migration of adult female white sharks (Carcharodon carcharias) reveals widely separated nursery areas and conservation concerns. Animal Biotelemetry 1(1), 2. https://doi.org/10.1186/2050-3385-1-2 (2013).Article
ADS
Google Scholar
Jacoby, D. M. P., Croft, D. P. & Sims, D. W. Social behaviour in sharks and rays: Analysis, patterns and implications for conservation. Fish Fish. 13(4), 399–417. https://doi.org/10.1111/j.1467-2979.2011.00436.x (2012).Article
Google Scholar
Palacios, M. D. et al., Manta and devil ray aggregations: conservation challenges and developments in the field, Frontiers Media S.A. https://doi.org/10.3389/fmars.2023.1148234. (2023).Pratt, H. L., Pratt, T. C., Knotek, R. J., Carrier, J. C. & Whitney, N. M. Long-term use of a shark breeding ground: Three decades of mating site fidelity in the nurse shark, Ginglymostoma cirratum. PLoS ONE 17(10), e0275323. https://doi.org/10.1371/journal.pone.0275323 (2022).Article
CAS
PubMed
PubMed Central
Google Scholar
van Zinnicq Bergmann, M. P. M. et al. Elucidating shark diets with DNA metabarcoding from cloacal swabs. Mol. Ecol. Resour. 21(4), 1056–1067. https://doi.org/10.1111/1755-0998.13315 (2021).Article
CAS
PubMed
Google Scholar
Download referencesAcknowledgementsWe would like to thank the staff of the Maui Division of Aquatic Resources for logistical support for the Maui fieldwork component of the study. We are especially grateful to Daniel Coffey, Melanie Hutchinson, and James Anderson for their contributions to the fishing and tagging efforts that resulted in this data set, as well as the many volunteers who helped with collecting the acoustic and visual humpback whale data. Special thanks to the Hawaii Institute of Marine Biology.FundingWe thank the Hawaii Department of Land and Natural Resources and the Pacific Islands Ocean Observing System for funding this study.Author informationAuthors and AffiliationsHawaiʻi Institute of Marine Biology, University of Hawaiʻi at Mānoa, 46-007 Lilipuna Rd, Kaneohe, HI, 96744, USAPaige Wernli, Mark Royer, Anke Kügler, Kim Holland & Carl MeyerHawaiian Islands Humpback Whale National Marine Sanctuary, NOAA, Kihei, HI, USAMarc LammersAuthorsPaige WernliView author publicationsSearch author on:PubMed Google ScholarMark RoyerView author publicationsSearch author on:PubMed Google ScholarAnke KüglerView author publicationsSearch author on:PubMed Google ScholarMarc LammersView author publicationsSearch author on:PubMed Google ScholarKim HollandView author publicationsSearch author on:PubMed Google ScholarCarl MeyerView author publicationsSearch author on:PubMed Google ScholarContributionsPW analyzed the data and wrote the first draft under the direct supervision and guidance of CM, who continued to review and edit subsequent drafts. MR and KM reviewed and edited subsequent drafts as well as suggested further analyses, ML and AK reviewed and edited subsequent drafts, provided data, as well as suggested further analyses. All authors substantially contributed to the conception/design of this work and have approved this submitted version.Corresponding authorCorrespondence to
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Reprints and permissionsAbout this articleCite this articleWernli, P., Royer, M., Kügler, A. et al. Telemetry reveals potential mating aggregation behavior of tiger sharks (Galeocerdo cuvier) in Hawaiʻi.
Sci Rep 15, 44076 (2025). https://doi.org/10.1038/s41598-025-27742-yDownload citationReceived: 23 July 2025Accepted: 05 November 2025Published: 18 December 2025Version of record: 18 December 2025DOI: https://doi.org/10.1038/s41598-025-27742-yShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
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KeywordsDiel patternsElasmobranchHawai ‘iPartial migrationPhilopatryPredator-prey interactionsReproductive ecologySeasonal movementsSite fidelitySpatial ecology More
