From a boat and from the air: size and composition of humpback whale groups estimated by onboard observers and drone videosABSTRACT
This study compared the size and composition of humpback whale groups estimated from boat-based observations and drone video analysis during the 2022 and 2023 breeding seasons in Ilhéus, Brazil. Data from 43 groups showed that drone consistently recorded larger group sizes than boat-based observations, with a strong positive correlation between the two methods (r=0.94, p<0.001). Drone also enabled more accurate identification of group composition, detecting additional individuals and more complex group types - such as large competitive groups - than the boat-based method. A significant association between method and group composition was found (p<0.001), with drones identifying more groups composed of four or more adults or a mother-calf pair with several escorts. These findings underscore the advantages of drone-based surveys for improving assessments of group structure, contributing to more accurate data to monitor and conserve cetacean populations.
Keywords:
Monitoring methods; Megaptera; Breeding ground; UAV
Humpback whales (Megaptera novaeangliae) are found in all oceans. They migrate annually from high-latitude feeding grounds to tropical and subtropical waters to mate and give birth (Clapham and Mead, 1999). In the Southern Hemisphere, seven breeding stocks are recognized by the International Whaling Commission (2002). Stock “A” reproduces in Brazilian waters (30°S to 5°S) from June to October (Andriolo et al., 2006; Wedekin et al., 2010). In Brazilian waters, the Abrolhos Archipelago (17°S) on the Abrolhos Bank has long been recognized as the area with the highest concentration of humpback whales during breeding season, particularly for calving (Andriolo et al., 2006). Although the Ilhéus shelf (14.8°S) lies outside the Abrolhos bank, it is increasingly used by humpback whales during breeding season (Gonçalves et al., 2018; Righi et al., 2024) and may serve as a peripheral reproductive area. Investigating group structure and behavior in such areas contributes to a broader understanding of Stock “A” spatial ecology and has implications for conservation and whale-watching management along the Brazilian coast. Breeding areas are characterized by small fluid groups (Mobley Junior and Herman, 1985), as well as larger dynamic groups of aggressive males competing for access to females, sometimes in the presence of calves (Clapham et al., 1992).
Accurately estimating the size, composition, or behavior of cetacean groups is challenging due to their underwater activity and the limitations of surface-level observation. This also applies to humpback whale groups, particularly in breeding areas, in which environmental conditions and whale behavior often limit visual assessments. Traditional methods rely on scan sampling (Altmann, 1974), in which observations estimate group characteristics from boat-based or land-based stations. However, these observations are limited by distance, visibility, and the difficulty of distinguishing individuals in large active groups (Mann, 2006). Exhalations, surface activity, and underwater behavior make counts even more challenging.
The emergence of drones has revolutionized marine mammal research by providing aerial perspectives that overcome the limitations of traditional methods. Drones improve data collection by enabling precise animal detection and providing access to previously inaccessible areas, such as remote islands and shallow rocky waters (Klemas, 2015). Drones provide high-resolution video recordings, enabling precise counts and detailed analysis of group composition and behavior (Fiori et al., 2017; Oliveira et al., 2023). They also enable continuous whale tracking from stable overhead views with minimal disturbance (Rebolo-Ifrán et al., 2019). Humpback whales socializing and nurturing are correctly identified by drones but not by trained observers (Fiori et al., 2019). Similarly, Torres et al. (2018) have employed drones to document novel foraging tactics, social interactions, and nursing by gray whales (Eschrichtius robustus) that were missed by traditional boat-based observations.
This study compares the effectiveness of drone-based video analysis and onboard visual estimation for assessing humpback whale group size and composition. By addressing methodological limitations and leveraging drone technology, we aim to improve the accuracy and reliability of marine mammal research in breeding areas.
This study was conducted along the coast of Ilhéus, Bahia, Brazil (14°47’S, 39°02’W), from June to November during the 2022 and 2023 breeding seasons (Figure 1A). Ilhéus is located 350 km north of Abrolhos Archipelago and has a narrow continental shelf with a 100-meter isobath 18 km from the coast. This narrow neritic zone facilitates whale-watching tourism by bringing humpback whales close to coast during the breeding season (Gonçalves et al., 2018). Data were collected opportunistically during commercial whale-watching tours aboard a 6.5-meter-long Top Fish 21 center console vessel operated by a licensed biologist. The boat is equipped with a 150-hp Mercury Optimax two-stroke outboard engine with a capacity for seven passengers and one crew member (Figure 1B). A total of 81 daytime trips were conducted under favorable sea conditions (Beaufort scale≤4), following a standard three-hour schedule and guided by daily forecasts from the GFS 13 climate model (NOAA, 2018). Although data collection took place during tourism operations, group observations and drone flights were coordinated by trained researchers using standardized protocols.
(A) Map of the study area and locations of humpback whale groups visually monitored from a boat and filmed using a drone during the 2022 (N=27) and 2023 (N=16) breeding seasons off Ilhéus, Bahia, Brazil. (B) Whale-watching boat used for visual observations and drone-based data collection. (C) Humpback whale observed from the boat. (D) Drone camera screenshot showing a group of humpback whales.
In compliance with Brazilian regulations, the boat maintained a minimum distance of 100 meters from the whales, with observation times limited to 30 minutes for adult groups and 15 minutes for groups with calves (IBAMA, 1996; Silva Júnior et al., 2019). A group was defined as one or more individuals within 100 meters of each other moving in the same direction or engaged in the same activity (Morete et al., 2008; Whitehead, 1983). This definition includes solitary whales, which were treated as individual groups and categorized accordingly during composition analyses. The calves were identified as individuals measuring one to two-thirds the body length of the accompanying adult (Herman and Antinoja, 1977; Mobley Junior and Herman, 1985).
The boat traveled at a speed of 20 to 25 km/h while searching for whales. When approaching within 300 meters of the whales, it reduced its speed to 5-9 km/h, enabling the observer to conduct a scan sampling without binoculars to estimate group size and composition. If whales were within 100 meters, the boat adjusted its course to maintain a 100-meter distance whenever possible or shifted the engine to neutral. For fast-moving groups, scan sampling was conducted at a greater distance - up to a maximum of 300 meters - at speeds of up to 15 km/h for safety reasons. The group categories included: solitary adult (S); dyad of two adults (DYAD); trio of three adults (TRIO); competitive group of four or more adults (TRIO+); a mother and a calf (MOC); a mother, a calf, and one escort (MOCE); a mother, a calf, and multiple escorts (MOCE+); two mothers and two calves (2MO2C); and two mothers, two calves, and one escort (2MO2CE). Each group was assigned to a single category based on the most specific configuration observed during the encounter. The classifications were mutually exclusive, and priority was given to more detailed groupings when possible (e.g., a group identified as MOCE+ was not simultaneously considered a MOCE). When uncertainty arose during observation, the classification defaulted to the less specific category to avoid overinterpretation.
Immediately after the scan sampling, a DJI Mini 2 drone was deployed to record video footage of the groups from a minimum altitude of 30 m above the water surface to comply with the authorization from Instituto Chico Mendes de Conservação da Biodiversidade (SISBIO process no. 81431-1) and to minimize disturbance to the animals (Christiansen et al., 2016; Fiori et al., 2019) and maintain a wide field of view for group assessment. The drone was equipped with a 12 MP sensor and capable of recording 4K video at 30 fps, operated with six batteries, each providing a maximum flight time of 30 minutes (Figure 1D). The camera was positioned vertically (90°) above the group to ensure that the entire group fit the frame. The zoom function was ignored. Small angle adjustments were occasionally made to reduce sun glare reflecting off the water. A total of 37 flights were conducted in 2022 and 16 in 2023. When groups remained close to the vessel and observation time was within the regulatory limits (less than 30 min for a group of adults and 15 min for a group with calves, [IBAMA, 1996]), a second drone flight was occasionally conducted over the same group to optimize data collection. All flights were carried out under favorable weather conditions (Beaufort scale≤3: winds≤19 km/h, waves≤1.3 m, no rain), and were limited by the time the boat could remain near the whales, following national whale-watching regulations (IBAMA, 1996), and by the need to recover the drone with at least 50% battery to ensure safe landing. The time spent near each group (15 or 30 minutes, see above) ensured that all individuals were recorded by the onboard observer before moving to another group. This approach minimized the risk of over or underestimating group size and composition. Group size and composition were recorded by the onboard observer during visual scan sampling, whereas those captured by drone footage were later estimated via video analysis.
A Pearson correlation coefficient was computed to assess the linear relationship between group size estimates obtained via drone-footage (hereafter “drone”) and direct visual scan sampling (hereafter “scan”). The mean group sizes estimated by the two methods were compared for each year (2022 and 2023) using paired-sample t-tests on log-transformed data after verifying normality (D’Agostino-Pearson test) and homoscedasticity (F-tests). Additionally, the proportion of groups in each category recorded by the drone and scan was compared using the Fisher’s exact test for count data. All statistical analyses were performed on R (R Core Team, 2024, version 4.2.3).
Size and composition were estimated for 43 groups using both methods. A very strong positive correlation was found between group size estimates derived from scan sampling and drone video analysis, r (41)=0.94, p<0.001 (Figure 2A). The drone estimated a broader group size range (1-12 individuals) than the scan (1-7 individuals).
(A) Scatter plot with linear regression (solid black line) between humpback whale group sizes estimated by visual scans and drone video analysis (Pearson: r=0.41, p=<0.001). The dashed line corresponds to X=Y. The size of each circle represents the frequency of occurrences for each pair of group size estimates. (B) Stacked bar plot showing the number of humpback whale groups by category as estimated by drone and visual scan. Groups with calves: MOC (one mother and one calf), MOCE (one mother, one calf, and one escort), MOCE+ (one mother, one calf, and multiple escorts), 2MO2C (two mothers and two calves), and 2MO2CE (two mothers, two calves, and one escort). Groups without calves: TRIO+ (competitive group of four or more adults), TRIO (three adults), DYAD (two adults), and S (solitary adult). Arrows indicate groups that were categorized differently by each method.
The drone consistently detected larger group sizes than visual scan in both years. In 2022 (n=27 groups), the mean group size estimated by drone was 3.89±2.41, compared to 3.19±1.33 by scan (one-tailed paired t-test: t=1.71, df=26, p<0.01). In 2023 (n=16 groups), the mean group size estimated by drone was 2.94±1.12, whereas the scan sampling method estimated 2.63±0.81 (one-tailed paired t-test: t=1.75, df=15, p=0.01). These results indicate that the drone method more comprehensively assessed group size than boat-based visual estimates.
The Fisher’s exact test showed a significant association between the observation method and assigned group composition categories (p<0.001). Although both methods found the same groups as having or not having calves, discrepancies arose in the classification of adult groups. In seven instances, the drone detected more individuals than the scan: four of the seven trios identified by the scan were classified as TRIO+ by the drone, one dyad was reclassified as a trio, one MOCE group was categorized as MOCE+, and another MOCE was identified as 2MO2CE. A single solitary individual was recorded and estimated consistently by both methods (Figure 2B). These discrepancies highlight the ability of drone-based methods to improve the detection of additional group members, especially in more complex compositions, and reinforce their value to estimate group size and to accurately identify social structure.
The composition of humpback whale groups is highly transient, particularly during the breeding season. However, we observed no changes in group composition, probably because our observation time of no more than 30 minutes was much shorter than the rate of change of 0.1 to 0.2 individuals per hour observed in Hawaiian waters (Mobley Junior and Herman, 1985). Previous studies have documented a high turnover of individuals within social aggregations, which are typically short-lived and reflect male-male competition and female mate choice (Baker and Herman, 1984; Mobley Junior and Herman, 1985). This turnover frequently results from males actively displacing rivals from the vicinity of sexually receptive females, a behavior that highlights the intensity of reproductive competition and contributes to group instability (Baker and Herman, 1984). In this context, song plays a central role as a mechanism of communication and social coordination, functioning as an acoustic signal of attraction and competition among males (Darling et al., 2006; Herman, 2016). Singing behavior may also contribute to synchrony and the temporal organization of breeding groups by mediating male-male interactions and influencing female mate choice (Herman, 2016).
More groups of whales were recorded in August and September (Figure 3, Table 1), which is consistent with the literature indicating that these months represent the peak of the reproductive season on the Brazilian coast (Gonçalves et al., 2018; Righi et al., 2024). TRIO and TRIO+ were commonly observed at the peak of the breeding season in August and September (Figure 3A, Table 1), during which pregnant females and females available for reproduction are found associated with adult males (Baker and Herman, 1984). Groups with calves were more frequently observed at the end of the breeding season (Figure 3B, Table 1) as reported in Hawaiian wintering grounds (Herman and Antinoja, 1977; Mobley Junior and Herman, 1985) because pregnant females migrate later than resting females to breeding sites as they spend more time feeding to save energy for calf birth and care (Dawbin, 1966).
Clustered stacked column chart showing the number of humpback whale groups by category as estimated by drone and visual scan according to two-month periods corresponding to the beginning (June-July), the middle (August-September), and the end (October-November) of the breeding season. (A) Groups without calves: TRIO+ (competitive group of four or more adults), TRIO (three adults), DYAD (two adults), and S (solitary adult). Arrows indicate groups that were categorized differently by each method. (B) Groups with calves: MOC (one mother and one calf), MOCE (one mother, one calf, and one escort), MOCE+ (one mother, one calf, and multiple escorts), 2MO2C (two mothers and two calves), and 2MO2CE (two mothers, two calves, and one escort).
Composition of humpback whale groups recorded by onboard observers and by drone videos throughout the breeding season (2022 and 2023) in Ilhéus, Bahia.
Groups with calves tend to stay close to the coast as a strategy to avoid predators and groups of males that may represent a danger to the calf (Baker and Herman, 1984; Gonçalves et al., 2018). Groups with calves are concentrated near the coast in the study area (Gonçalves et al., 2018) due to the narrowness of the neritic zone, which facilitates their observation by tourist boat navigating up to 20 km from the coast. These females attract breeding males, who are also regularly observed near the coast.
Our results confirm that drone-based observations more accurately estimate humpback whale group sizes than visual scans, consistently showing larger groups. This finding is in line with previous studies on the superiority of drones over traditional marine animal counting methods, reducing the common underestimations associated with visual observations (Choi et al., 2021; Hodgson et al., 2017; Oliveira et al., 2017). In Fettermann et al. (2022), drone-based dolphin counts were 26.4% higher per group than boat-based ones, with a substantial number of underwater behaviors detected by drones that boat observers missed. The size and organization of the group reflect habitat use, and the ecological role of the species is influenced by food availability, social interactions, and defense against predators (Hooker and Gerber, 2004). These results reinforce that drones have introduced a new perspective for cetacean observation, improving individual counts and increasing the accuracy of group composition identification (Fiori et al., 2017).
One of the main sources of underestimation in visual monitoring is the difficulty in detecting all individuals within a group, particularly in complex formations. This is evident in our results: although both methods correctly identified the presence or absence of calves, discrepancies arose in the classification of seven out of the nine group categories. The drone consistently detected more adults than visual scans, leading to differences in group categorization. Fettermann et al. (2022) compared the sizes of 21 bottlenose dolphin groups using both scan and drone methods, finding that size estimates matched for only two small groups. This result underscores the difficulty of determining group size based on visual observation, particularly in complex formations. This raises concerns about the validity of detailed group classifications in visual-based studies as our findings suggest that this method often underestimates the actual number of individuals and may also misrepresent their sex and age composition.
An important aspect to consider is the relationship between group size and counting accuracy. The larger groups were more easily detected than the smaller ones, likely due to their higher surface activity and shorter breathing intervals (Clapham et al., 1992). These factors make continuous monitoring and filming easier. However, accurately counting individuals in large groups remains a challenge as they are often clustered together, resulting in visual overlaps on aerial images and making it difficult to distinguish each animal. This is more noticeable in visual monitoring, in which it is harder to count the exact number of individuals due to a limited field of view. The use of drones to detect cetaceans and estimate group size, behavior, and health is widely studied (see Álvarez-González et al. (2023) for a review) but future studies could assess the relationship between the size of large whale groups and the accuracy of individual counts on a fine scale using drones.
The greater accuracy of drones in identifying group composition also has significant biological implications. Groups consisting of two mothers and two calves (with or without an escort) are rarely documented, and previous studies indicate that such configurations are often avoided by females, possibly to reduce the risk of nursing non-filial calves (Mobley Junior and Herman, 1985; Tyack, 1982). Multiple mother-calf groups have been recently reported along the east coast of Australia and may play a role in the social development of calves (McGovern et al., 2025). Drones can greatly help document such rare group composition and offer new insights into their occurrence and function.
The tendency for mothers and calves to remain close to the coast indicates that the continental shelf in Ilhéus is an important area from August onward. The proximity of groups with calves to the coast increases the likelihood of interactions with tourist boats, with potentially negative impacts for these more vulnerable groups. Moreover, the presence of larger groups with competitive males in the same region intensifies social activity and the potential stress for mothers. In humpback whale behavior studies under vessel disturbance, the intensity of their response varies depending on group size and composition (Dunlop, 2024; Schaffar et al., 2009; Tyack and Whitehead, 1982). Tourist observations may consider these temporal and spatial dynamics, increasing attention during navigation (especially during the peak and the end of the season) and respecting the legislation. Drones can help detect neonates and calves and assist the decision of a tour boat operator whether and how long to approach a group.
This study shows that drones provide a more accurate and detailed assessment of humpback whale group size and composition than traditional boat-based visual methods. Our results showed that drone consistently detected larger group sizes and identified complex group compositions - including rare multi-mother-calf compositions - that are often overlooked in standard observations. These findings underscore the value of incorporating drone-based techniques into marine mammal monitoring, with significant implications for ecological research, population assessment, and the management of whale-watching activities.
Moreover, our findings suggest that conventional group classification schemes may require revision as visual methods tend to underestimate group complexity, particularly in larger aggregations. By refining survey methodologies and integrating drone technology into long-term monitoring efforts, future research can enhance our understanding of humpback whale social behavior and contribute to more effective conservation strategies.
While some technical limitations were encountered - such as glare affecting visibility and environmental constraints in drone deployment - these challenges can be mitigated by proper equipment and planning. Overall, our study supports the growing use of aerial surveys as a powerful tool in cetacean science.
SUPPLEMENTARY MATERIAL
The authors declare that there are no supplementary materials associated with this article.
DATA AVAILABILITY STATEMENT
All data are available from the corresponding author upon reasonable request.
ACKNOWLEDGMENTS
We would like to thank the Graduate Program in Zoology at Universidade Estadual de Santa Cruz and the Aquatic Mammals Laboratory for their logistical support. We are also grateful to Ecosul Turismo and the whale watchers who funded most of the data collection trips. We also thank the anonymous reviewers for their constructive comments and suggestions, which helped improve the quality and clarity of the manuscript.
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AI USE DISCLOSURE:
The authors declare that no generative artificial intelligence tools were used in the preparation, writing, or analysis of this manuscript.
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FUNDING:
This research was funded by a scholarship from the Brazilian Federal Agency for Support and Evaluation of Graduate Education - Brazil (CAPES), a scholarship from State Funding Agency of Bahia (FAPESB), as well as by two grants from the Animal Behavior Society and Idea Wild [DA SBRAZ0122]. AL received a postdoctoral fellowship from Universidade Estadual de Santa Cruz (PROBOL-UESC).
