No place like home: assessing the multidimensional habitat use of endangered Arabian Sea humpback whales (Megaptera novaeangliae, Borowski 1781) with satellite telemetry

Abstract

The Arabian Sea humpback whale (Megaptera novaeangliae; ASHW) is understood to be the only population of this species that does not undertake long-range seasonal migrations between high- and low-latitude waters. Until recently, understanding the movements and range of individual ASHWs has relied mainly on comparisons of dorsal fin and tail-fluke images archived in photo-identification catalogues and on observations made during small-vessel surveys off the coast of Oman since 2000. The ASHW population is classified as Endangered by the IUCN Red List of Threatened Species, with an estimated 82 individuals off Oman’s coast (95% CI: 60–111), and faces increasing anthropogenic threats throughout its known range. To better understand the spatial ecology of this population, 14 Argos-enabled satellite tags were attached to ASHW off the Arabian Sea coast of Oman between February 2014 and December 2017. Individuals were tracked for a total of 749 days (mean=53, SD = 42, range=18–163 days) producing 484 days of depth-use data (mean=44, SD = 26, range=15-87). Home ranges extended along the western Arabian Sea coastline of northern Yemen and southern Oman, with a core area in the Gulf of Masirah (Oman). Switching state-space models revealed predominant area restricted search behavior (associated with breeding and foraging behavior) over continental shelf areas, with transiting movements occurring further offshore. The widest-ranging individual (a female, tag longevity 120 days) completed a round trip across the Northwest Indian Ocean between the Gulf of Masirah and the Gulf of Mannar (India). The track of this animal, and others along the coast of Oman, revealed an overlapping relationship between ecological drivers related to habitat use, including foraging and breeding, with fishing and shipping activities. The findings demonstrate the unique ecology of ASHW compared to other humpback whale populations and underscores the need for national and international authorities to incorporate these results into management initiatives to safeguard this small and Endangered population.

1 Introduction

Biologging has enabled the remote monitoring of free-ranging species that are difficult to observe, allowing for the study of physiology, behavior and energetic states (Cooke et al., 2004; Rutz and Hays, 2009; Hays et al., 2019; Hawkes et al., 2021; Holton et al., 2021). The application of this technology has been valuable for defining the movement of large whale species of conservation concern, for example western gray whales (Eschrichtius robustus; Lilljeborg, 1861), North Atlantic right whales (Eubalaena glacialis; Müller, 1776) and Antarctic blue whales (Balaenoptera musculus intermedia;Burmeister, 1871) (e.g. Heide-Jorgensen et al., 2001; Baumgartner and Mate, 2005; Andrews-Goff et al., 2013). Biologging has been used extensively to study humpback whales (Megaptera novaeangliae), revealing insights into their ecology, including energy budgets during long distance migration (e.g. Braithwaite et al., 2015; Riekkola et al., 2020; Kettemer et al., 2022), localized habitat use and long-distance movements (e.g. Zerbini et al., 2006; Kennedy et al., 2014a; Garrigue et al., 2015; Cerchio et al., 2016a; Dulau et al., 2017; Derville et al., 2020), relationships between dive behavior and foraging success (e.g. Friedlaender et al., 2013; Goldbogen et al., 2019) and the overlap of anthropogenic activities with important whale habitats (e.g. Rosenbaum et al., 2014; Guzman and Felix, 2017; Aschettino et al., 2020).

Humpback whales are capital breeders, generally undertaking long distance migrations between high-latitude foraging grounds and low-latitude breeding grounds (Chittleborough, 1958; Jönsson, 1997, Clapham, 2002, Stephens et al., 2009; Stern and Friedlaender, 2018). However the Arabian Sea humpback whale (ASHW) is an exception. Evidence from sightings data indicate the year-round presence of this species in the Arabian Sea (Brown, 1957; Slijper et al., 1964; Whitehead, 1985; Reeves et al., 1991; Minton et al., 2011, Moazam and Nawaz, 2019). This peculiarity has implications for our scientific understanding of the species, especially with regards to behavioral ecology and the challenges it presents to theories about drivers of baleen whale migration (Papastavrou and Van Waerebeek, 1997; Corkeron and Connor, 1999; Clapham, 2001).

The hypothesis that ASHWs are resident in the Arabian Sea year-round was confirmed by data from illegal Soviet whaling operations in the Arabian Sea (1964-1966). Examination of captured whales revealed the ASHW breeding cycle to be six months out of phase with Southern Hemisphere conspecifics and also revealed that whales, including pregnant whales, had been feeding on sardines and euphausiids whilst present in low-latitudes (Mikhalev, 1997). These data supported earlier hypotheses that the strong coastal upwelling generated by the southwest monsoon allows ASHWs to feed, mate and calve within the waters of the Arabian Sea (Reeves et al., 1991; Papastavrou and Van Waerebeek, 1997; Mikhalev, 1997).

Small vessel surveys conducted off the coast of Oman between 2000 and 2012 provided genetic and photographic evidence that ASHWs are isolated. Genetic data suggested ASHWs diverged from Southern Hemisphere populations ~70,000 years ago (Rosenbaum et al., 2009; Pomilla et al., 2014). Comparison of individual photographic identifications and male song between the Arabian Sea and the southwest Indian Ocean breeding population further indicated the lack of mixing and isolation of ASHWs (Minton et al., 2010; Cerchio et al., 2018). This limited range contrasts with the long-distance movements associated with other humpback whale populations known to migrate between high latitude summer feeding grounds and low latitude winter breeding and calving grounds (Reilly et al., 2008; Figure 1). This evidence of isolation, together with a mark-recapture abundance estimate of 82 individuals (95% CI: 60 to111), led to the determination of the ASHW as Endangered by the IUCN (Minton et al., 2008). Data from the same surveys in Oman allowed a preliminary evaluation of the spatial ecology of ASHWs (Minton et al., 2011). This work helped to inform spatial modelling analyses, which confirmed the importance of two areas of Oman’s coastal waters for the population: the Gulf of Masirah and the Hallaniyat Bay (Corkeron et al., 2011).

Figure 1

Photo-identification data from Oman indicates high re-encounter rates, as well as regular associations between some individuals in both the Gulf of Masirah and Hallaniyat Bay, areas less than 300 km apart (Minton et al., 2011; Willson et al., 2013). Foraging and breeding behaviors (including singing and competitive behavior) have been documented in both areas and there is some evidence that they also serve as calving areas, although sightings of calves are limited and more data is required to better understand the importance of different habitats for ASHW calving (Minton et al., 2011; Baldwin et al., 2011; Cerchio et al., 2018; Willson et al., 2018).

Whilst studies since 2000 have continued to indicate that the ASHW population does not undertake seasonal latitudinal migrations, records of similar songs and an opportunistic photographic re-sighting of an individual present in Oman and Indian waters, suggests that at least some individuals range between the western and eastern Arabian Sea and the Laccadive Sea (Whitehead, 1985; Cerchio et al., 2018; Anderson et al., 2022). Concerns with the conservation status of the ASHW population have motivated collaborative research and conservation efforts throughout much of their range (Minton et al., 2008; IWC, 2011; CMS, 2017). There is abundant evidence that globally-documented threats to baleen whale populations (e.g., ship strikes, underwater noise and fisheries interactions (Vanderlaan and Taggart, 2007; Van Waerebeek and Leaper, 2008; Richardson et al., 2013; Thomas et al., 2016), are present and escalating in the range of the ASHW population (Minton et al., 2011; Baldwin et al., 2015; Willson et al., 2016; Dakteh et al, 2017; Sutaria et al., 2017; Thomas et al., 2016; Anderson et al., 2020; Minton et al., 2022) and yet still relatively little is known about their magnitude or effect. A growing concern for the consequences of these threats to ASHWs and the need for data to better inform decision making led the International Whaling Commission’s (IWC) Scientific Committee to recommend further investigation of ASHWs using satellite telemetry techniques (IWC, 2011; IWC, 2013).

This study presents patterns of ASHW movement from satellite tracking of whales in Oman between 2014 and 2017, focusing on horizontal and vertical spatial use of habitats with reference to their behavioral ecology.

2 Materials and methods

2.1 Boat surveys and satellite tagging

Four boat-based surveys to locate humpback whales for tagging were conducted in the Hallaniyat Bay Feb-Mar.; 2014 & 2015) and in the Gulf of Masirah (Nov. 2015 & 2017; Figure 2 and 3). The area of the surveys and timing were determined based on the findings of previous vessel-based surveys in order to maximize encounters with whales. In the Hallaniyat Bay, surveys took place between early February and mid-March, coincident with the peak of the breeding season, while in the Gulf of Masirah they occurred from mid- to late November, coinciding with the early phase of the breeding season (Mikhalev, 1997; Minton et al., 2011; Corkeron et al., 2011). Observers searched for whales from two 6.5 m rigid-hulled inflatable boats (RHIBs) during paired parallel transect surveys separated by 3–4 km. Data collection was consistent with previous sightings-based survey protocols in Oman (Minton et al., 2011; Corkeron et al., 2011). Visual searching was supported by use of omni-directional dipping hydrophones (HTI-96-MIN, High Tech Inc.) deployed from both vessels to guide them towards singing males. Search effort along the Dhofar coastline was restricted to inshore areas due to security concerns related to piracy, and was supported by cliff-top observers guiding vessels to sightings using VHF radio (Willson et al., 2013). During tagging operations, one RHIB was dedicated to the deployment of satellite tags, biopsy sampling and photo-identification, while the other performed support and safety functions in accordance with recommended best practices for cetacean tagging (Andrews et al., 2019; Hassel et al., 2022).

Figure 2

Figure 3

Calabrese et al., 2016) and derived from the Ornstein-Uhlenbeck Foraging (OUF) anisotropic model.

Argos satellite tags with fully integrated housings and attachment systems (Zerbini et al., 2025) SPLASH-302, SPLASH-373 and SPOT-303 (Wildlife Computers, Redmond, WA, USA) were used for tracking. These tags gathered data on dive duration, maximum dive depth and dive shape. Each transmitter was contained within a cylindrical, surgical-grade stainless steel housing. Tag anchors were designed to penetrate the epidermis and blubber and to attach at or below the underlying connective tissue fascia. All external components of the tag were disinfected and stored in a sterile container prior to deployment. Endorsement of the study was obtained from the IWC Scientific Committee and tag deployments were carried out in accordance with best practice protocols (IWC, 2011, IWC, 2020, Andrews et al., 2019). Several steps were taken to ensure the highest ethical practices and to minimize potential impacts on this Endangered species. All study protocols were evaluated by a group of experienced scientists within the IWC Scientific Committee; the effectiveness and impact of tag design was reviewed (Robbins et al., 2013), the principal investigator (AW) participated in a separate tagging project in Madagascar (Cerchio et al., 2016a) before attempting the Arabian Sea work; and researchers with requisite experience were contracted for tagging.

The physical health status of each whale considered for tagging was evaluated using signs of injury or emaciation. Attempts were made to identify targeted individuals in situ by comparison with the Oman humpback whale photo identification catalogue. Tag deployment was conducted from the modified bow of the tagging RHIB at distances of five to eight meters using the Air Rocket Transmitter system ‘ARTS’ (Heide-Jorgensen et al., 2001). A biopsy sample was collected simultaneously using a crossbow and dart (Lambertsen, 1987). Biopsy samples have been routinely collected during surveys in Oman as a genetic marker for individuals and for confirming the sex of sampled animals (Minton et al., 2011; Pomilla et al., 2014). Video and photographic records were collected throughout the tagging process. Vessels followed tagged whales for a minimum of one hour after each tagging event to record behavior and further photograph the tag site. Tagged whales that were resighted at any time in subsequent days or years after their tagging event were approached for additional photographs to document potential tag movement, if the tag was still implanted, and healing (Minton et al., 2022).

Satellite tags were programmed based on an anticipated deployment duration of six months. This process was informed by previous tagging studies of humpback whale populations elsewhere in the world (Zerbini et al., 2006; Kennedy et al., 2014a, Kennedy et al., 2014b). Tag transmissions were duty-cycled to coincide with Argos System satellite overpasses and to transmit within four-hour blocks three times per day. Transmissions were restricted to a maximum of 400 messages within a 24-hour period. The daily transmission schedules of tags deployed in the first two field seasons (2014 and 2015) were modified from the 31^st of May onwards to every second day, with the objective of maintaining sufficient power to capture movements during the Arabian Sea southwest monsoon period (May-September).

2.2 Switching space-state model data processing

To provide spatially and temporally comparable data among individuals, Argos system location data were processed using a behaviorally switching space-state model (SSSM) (Jonsen et al., 2005, Jonsen et al., 2007; Breed et al., 2009). Location class (LC) fields were filtered with Z and 0 classes removed (Witt et al., 2010), and no subsequent filters were applied (e.g. speed and turning angle filters).

SSSM modelling parameters were estimated for each whale independently using Markov Chain Monte Carlo (MCMC) methods (Jonsen et al., 2005; Breed et al., 2009) and implemented in R v.3.2.3 and RStudio (R Core Team, 2015; RStudio Team, 2015) and WinBUGS v.1.4 (Lunn et al., 2000), using Argos-derived locations from each tag. The procedure generated a model of observation error and a mechanistic model of animal movement that were solved simultaneously during data processing (Jonsen et al., 2005). A correlated random walk model was used, which switches between two behavior states, either Area Restricted Search (ARS; state 2) or Transiting (TRN; state 2). ARS is suggestive of foraging, resting, or breeding behavior (Bailey et al., 2009), represented by higher rates of turning within focal areas.

The duty cycle (operational periods) of satellite tags and temporal gaps between received locations were investigated in test runs of the SSSM, resulting in the selection of a time step interval of 8 hours in the final model runs. The model was run with two MCMC chains for 10,000 iterations after a burn in of 5,000, and behavior state classification was based on four parameters: i) mean turning angle for area restricted search mode, ii) mean turning angle for transiting mode, iii) autocorrelation in speed and direction for area restricted search mode, and iv) autocorrelation in speed and direction for transiting mode (Jonsen et al., 2003; Jonsen et al., 2005). A conservative approach was applied to assigning model values between three classification states: ARS (1-1.25), TRN (1.75-2) and UND (1.26 and 1.74; Jonsen et al., 2007; Garrigue et al., 2015).

Further spatial analyses were performed using point counts of the different SSSM behavior modes within pre-defined areas of interest in <200 m water depth, including: the Gulf of Masirah, Sawqirah Bay (between Masirah Island and Hallaniyat Bay); Dhofar; the area to the south of 17° N; and areas with water depths >200 m (Supplementary Figure 1).

2.3 Home range analysis

Continuous Time Movement Modelling (CTMM) was applied to filtered Argos location data to evaluate habitat use (Fleming et al., 2014, Calabrese et al., 2016, Calabrese et al., 2020). Implausible locations based on speed and turning angles were removed through the ‘sdafilter’ from the R package ‘argosfilter’ (Freitas et al., 2008) along with location classes 0 and Z. Default parameters of this package were used, except speed, limited to 12 km hr^-1 based on plausible maximum swimming speeds of humpback whales (Garrigue et al., 2015). The filtering work was performed in R v.3.2.3 (R Core Team, 2015), with data archived in Movebank (Wikelski et al., 2020) to enable integration with the CTMM Shiny R web application (Dong et al., 2019). The Ornstein-Uhlenbeck Foraging (OUF) anisotropic model of space-use was selected from the CTMM package and used to produce an Autocorrelation Kernel Density Estimate (AKDE). This model accounts for the biases from spatial and temporal autocorrelation (i.e. spatially and temporally non-independent data) inherent in satellite telemetry data (Fleming et al., 2014). AKDE isopleths were produced at the 0.95 and 0.5 utilization distribution, with these representing the home range (HR) and core home range (CHR), respectively. Final home range analysis was conducted in ArcMap 10.7 (ESRI, 2019) by preparing composite maps of the two different utilization distribution levels. The home ranges were combined in a single map with the sum of overlapping polygons from individuals used to represent the overall home range importance for the study group (Irvine et al., 2014). This technique was applied to both 95% and 50% isopleths.

2.4 Depth use

SPLASH MK-10 tags provided dive histogram data at 24 h intervals on the percentage time spent within pre-defined depth ranges and frequency of dive durations occurring within pre-defined limits (minutes). Tags also recorded dive events, including the time and date, duration, maximum depth (meters) and shape of individual dives according to generalized geometry (e.g. square, V and U). Dive events were only logged if they were >1 min in duration and >15 m in depth. Once each 24-hour period was complete the archived data were retained in the tag memory for a period of two days and relayed via the Argos System. Dive event data were pooled into hourly bins for plotting and evaluation of diurnal trends. Dive histogram data were summarized as median and interquartile range statistics (IQR) with the dive shape and duration data presented using the mean and standard deviation (Wickham, 2011).

Location and associated behavioral state data from the SSSM process were matched with dive duration, dive depth and dive shape data where they occurred within ±1 hour of each other. The seabed depth was extracted from GEBCO bathymetry data for all SSSM locations (GEBCO, 2019). To investigate the association between physical oceanographic features and dive characteristics, the dive depth location points were plotted together with a global seabed geomorphology raster dataset (Harris and Baker, 2019). Counts of SSSM locations were evaluated within polygons defined by the global seabed geomorphology raster dataset for shelf, escarpment, canyon and land features. SSSM locations occurring in >200m of water were used to investigate the relative difference between space use over escarpment and canyon features.

3 Results

3.1 Tagging

A total of 14 satellite tags with operational duration greater than one day were successfully deployed on 13 individual whales, (9 males, 2 females and 2 of unknown sex; labelled individuals A-N in Table 1). One of the males was tagged twice; once in February 2014, and again in March 2015 (animal code G and L). Six failed deployments were comprised of one miss, and five attempts where the tag failed to properly implant. Of these failed implants, the tag glanced the animal and/or fell off soon after the tagging attempt (within 24 hours of the tagging event). Tag data from failed deployments were not included in subsequent analysis. Results are reported as mean ±1 SD, unless otherwise specified. Tag operational duration was 53 ± 42 days (range=18-163) resulting in 309 ± 144 locations per individual (range=136-639). SPLASH MK-10 tags generated 44 ± 26 daily records of daily dive data (range=16-87) and 782 ± 542 dive events per individual (range=129-1775).

Six of 14 tags were deployed in the Hallaniyat Bay in February and March of 2014 and 2015 (SPOT5 n=3; SPLASH MK-10 n=3) and the remaining eight tags were deployed in the Gulf of Masirah in November of 2015 and 2017 (SPLASH MK10 n=8).

3.2 Horizontal movements

Of tags deployed in the Gulf of Masirah (November 2015 & 2017), five transmitted <35 days, revealing local scale movements of whales in the vicinity of the deployment site (individuals A, B, C, D and F). These individuals remained in area restricted search mode for the entire duration of tag transmission. Two whales tagged in mid and late November 2017 (individuals I & K) made journeys south to the Hallaniyat Bay and remained there for the duration of the remaining tracking period (Figure 2). All animals tagged in the Hallaniyat Bay in 2014 and 2015 (E, G, H, J, L, N) moved northwards between mid and late March and five travelled to the Gulf of Masirah (Figure 2). From this group, the whale with the longest transmission duration (individual N; n=163 days) travelled north to the Gulf of Masirah then to the east of Masirah Island before transiting south to Ras Abu Fartak in the waters of Yemen. One individual (animal codes G and L) made the same journey between the Hallaniyat Bay and Gulf of Masirah in 2014 and 2015, albeit in transiting rather than area restricted search mode in 2015 (Figure 2).

The widest ranging whale (individual M) remained in the Gulf of Masirah for 19 days after tag deployment (until mid-December 2017) (Figure 2, panel M insert a), then progressed in transiting mode east across the Arabian Sea. Location data were temporarily unavailable for seven days after traversing longitude 63^° E. A transmission was subsequently detected at 73° E over the continental shelf off the state of Goa in western India. The whale then moved south and arrived in the Gulf of Mannar in early January, where it remained until February (Figure 2, panel M insert b). During this time, the animal remained within 50 km of the most southerly point of India (adjacent to the town of Kanyakumari) and predominantly shoreward of the 50 m depth contour. This record provides the first direct evidence of an ASHW crossing the Arabian Sea. This individual subsequently made a return journey to the Gulf of Masirah, arriving in early March 2018. No transmissions were received during the return trans-oceanic crossing between 76^˚E and 58^˚E (close to Masirah Island) over a period of 29 days. The projected great circle route of this return movement was 1573 km and took 12 days, representing a minimum mean swim speed of 5.7 km h^-1. An estimated minimum distance of 7,330 km was covered in 103 days during the round trip between the Gulf of Masirah and Gulf of Mannar. At least 44 days and 1,693 km of the journey (defined by SSSM data) occurred over the continental shelf along the west coast of India. Gaps in location data during both east and west trans-oceanic crossing events are assumed to be caused by any number factors including limitations of satellite coverage, biofouling, sea state conditions (swell blocking transmissions) and the swimming behavior of the animal (limited exposure of the tag out of the water during the transit).

3.3 Switching space state modelling and home range habitat use

SSSM treatment of Argos tracking data resulted in 1,805 predicted locations across all tagged whales (Supplementary Table 1). The Gulf of Masirah remained an important habitat for individuals, with 57% of SSSM derived locations (n= 840, 64.6 ± 48.2, range=0-204) occurring within this area. All tagged animals, apart from individual J, spent at least some of their tracked time in this area. The Hallaniyat Bay encompassed 18% of locations (n=265, 37.9 ± 19, range=0 – 74) from eight individuals (E, G, H, I, J, K, L, N). The lowest occurrence of SSSM locations by area of 6% (n=110, 13.8 ± 15%, range=0-26%) occurred in Sawqirah Bay, involving the movements of the same eight individuals and captures the movements of whales passing through the area whilst transiting between the Gulf of Masirah and the Hallaniyat Bay. Waters >200m appeared less important for these tagged animals, with 13% (13.8 ± 16, range 0-210) of locations occurring in this depth zone. Individual N spent the most time offshore (47%) and least time in the Gulf of Masirah (11%).

The highest proportion of locations (83 ± 27%) were assigned to the area restricted search behavioral state, followed by unidentified (12 ± 21%) and transiting (5 ± 7%) (Supplementary Table 2). The highest percentage of area restricted search locations (51%) occurred in the Gulf of Masirah (n=1501, 40 ± 32.8), and the highest percentage of transiting locations (44%) occurred in regions with water depth >200 m (n=101, 3 ± 3) (Supplementary Table 3). Most locations (87.5% of the total) occurred in waters <200 m depth (n=1450, 104 ± 62). Within this depth zone, 85% of the locations were attributed to area restricted search (n=1258, 90 ± 55), while locations assigned to the same behavior mode were less dominant (51.5%) in water >200 m depth (n=355, 24 ± 50 per individual) (Supplementary Table 4).

The full extent of home range use (95% isopleth) in the western Arabian Sea extended from the most easterly point of the Arabian Peninsula (Ras al Hadd) to northern Yemen (Figure 3A). The widest home range was demonstrated by individual N, with the range extending between the north of Masirah Island to the eastern waters of Yemen. Six animals revealed home ranges between the area north of Masirah Island and Salalah, whilst the home range of 13 whales overlapped in the Gulf of Masirah (Figure 3A). Ten animals contributed to the core range (50% isopleth) between the north and central area of the Gulf of Masirah, the most important area for whales tagged in this study (Figure 3B).

3.4 Depth use, dives and duration

Depth use histogram data accumulated every 24 hours (cumulative=484 days, 44 ± 26, range=16–84 days) were obtained from 11 humpback whales (individuals A, B, C, D, E, F, I, K, L, M, N) (Figure 4). Some erroneous dive records were received, where dive duration exceeded 35 minutes, which is longer than any dives reported elsewhere for the species (Baird et al., 2000; Derville et al., 2020); as such, these 31 dive events were removed from analysis (0.36% of the total number of dive events). Histograms of dive duration revealed the maximum median value was recorded in the 5–9 minute duration bin (median=35 dives day^-1, IQR = 36) (Figure 4A, Supplementary Table 5). Time at depth histogram data revealed the highest median for percentage of time was recorded in the 0-9.9 m depth bin (median=49% IQR = 22%) and followed by the 10-19.9m depth bin (median=33%, IQR = 22%) (Figure 4B, Supplementary Table 6).

Figure 4

Dive event records (n=8,599), describing characteristics of individuals dives, were received from 11 whales instrumented with SPLASH MK-10 tags (782 ± 543, range=430-1,775) (Supplementary Table 7). The mean duration of dives was 7 ± 1.7 minutes (range=4.6-11.6) with a mean maximum dive duration of 25 ± 6.9 minutes (range=14.1-32). Mean dive depth across all individuals was 27 ± 7 m (range=20-41) and the mean of maximum depths was 167 ± 99 m (range=36-323) (Supplementary Table 7). Individuals made shallow dives (mean <50 m) between late afternoon and late evening (15:00 and 23:00) and deeper dives (mean >100 m) for remaining hours of the day (Figure 5A). Maximum dive depths >150 m were recorded between 03:00 and 11:00 (Figure 5A). Mean dive duration was greatest between 05:00 and 12:00 (Figure 5B).

Figure 5

Square shaped dive profiles were the dominant dive shape (64.2%, n=5,379, 489 ± 367), followed by U-shape (27.2%, n=2,278, 207 ± 162) and V-shape (8.6%, n=721, 65.5 ± 52.4) profiles, respectively (Supplementary Table 8). Square shaped dive profiles were consistently dominant when assessed across each behavior mode ranging between 65% and 57% (Supplementary Table 9). Greatest maximum (max=323m) and mean depths (40.2 ± 29.7m) were associated with TRN mode (Supplementary Table 10). Dives associated with area restricted search mode accounted for the greatest maximum duration (max=33.4, 5.72 ± 3.65); whereas transiting mode dives were associated with the greatest mean duration (max=32.02 min, mean=9.93 ± 5.72) (Supplementary Table 11). Analysis of dive depth and duration revealed differing dive frequency distributions associated with area restricted search and transiting behavior modes (Figure 6). Area restricted search modes were characterized by short shallow dives of 19 m and 3 minutes at the central isopleth (normalized isopleth value=1) (Figure 6A). Transiting mode dives exhibited a multi-modal form, with a broader distribution and characterized as shallow and short (21 m, 7.5 minutes, normalized isopleth= 0.8), shallow and long (22 m, 16 minutes, normalized isopleth=0.8) and deep and short (33 m, 5 minutes, normalized isopleth= 0.8) (Figure 6B). Dives over shelf areas (and associated with SSSM locations) presented a narrow IQR of 8 m and median depth of 21 m, whereas dives made over canyon and escarpment features were characterized by a broader IQR of 36 m and median depth of 32 m. (Figure 7). The distribution of mean dive depths referenced to SSSM locations revealed a predominance of shallow water dives <25 m occurring over shelf areas, particularly in the Gulf of Masirah and the Hallaniyat Bay (Figure 8). Deeper dives >50 m were recorded over canyon and escarpment features near shelf areas, as found off the east coast of Masirah Island (Figure 8A) and the Hallaniyat Bay (Figure 8B). 50% of SSSM locations in offshore waters (n=227) were over escarpment features (Supplementary Table 12), with 27% over canyons (n=121) and the remainder over other habitat types (23%, n=101).

Figure 6

Figure 7

Harris and Baker, 2019).

Figure 8

Harris and Baker, 2019). Simplification of transiting SSSM behavior mode pathways between areas is represented by blue lines for inshore commuting and red lines for offshore commuting.

4 Discussion

This study provides unprecedented insights into the horizontal and vertical habitat use of ASHWs, obtained from telemetry-based behavior modelling, home range analysis and investigation of depth use.

Three features of this study provide new and supporting evidence about the spatial ecology of ASHWs: i) the importance of the Arabian Sea coast of Oman for this Endangered population; ii) behavioral plasticity in switching between shallow and deep-water habitats in and surrounding the Gulf of Masirah; and iii) the ability to undertake long-distance longitudinal movements within their range.

4.1 Localized movements in the western Arabian Sea

ASHW home ranges and core home ranges were located in some of the most productive waters of the Arabian Sea, one of the world’s five major upwelling areas, where strong upwelling currents are generated during the south-west monsoon (Hitchcock et al., 2002; Piontkovski and Claereboudt, 2012; CBD, 2016). This range, which is within an Ecologically or Biologically Significant Marine Area, confirms the importance of the area as a predictable high trophic transfer hotspot (Hazen et al., 2013; CBD, 2016). ASHW preference for continental shelf and slope habitat, as indicated by area restricted search modes, was consistent with breeding and foraging related behavior described in other humpback whale populations (Chittleborough, 1965; Baker et al., 1986, Clapham, 2000, Fleming and Jackson, 2011; Dulau et al., 2017) and for ASHW, where foraging is considered to occur year round (Corkeron et al., 2011, Baldwin et al., 2011, Minton et al., 2011; Cerchio et al., 2016b). The study extends both the spatial range and understanding of ASHW habitat use by documenting highly localized transits along the shelf between areas previously described in other studies (individuals E, G, K, L and N) and further offshore in the western Arabian Sea (individuals H, I and N) (Minton et al., 2011; Willson et al., 2013).

A noteworthy aspect of these data is the relatively constrained range of the majority of tagged ASHWs, in comparison to other humpback whale populations. An example comes from two studies in the southwest Indian Ocean (the nearest neighboring population to ASHWs). These studies were conducted at the peak of the breeding season to document movements within the breeding grounds (Cerchio et al., 2016a; Dulau et al., 2017) as opposed to late in the season, where the objective was to document migratory destinations (e.g. Zerbini et al., 2006; Garrigue et al., 2010; Andrews-Goff et al., 2018). Despite this focus on breeding range movements, and relatively short tag transmission periods (means of 24.2 days and 25.7 days, respectively), whales tagged both off Madagascar (n=23) (Cerchio et al., 2016a) and off Reunion Island (n=15) (Dulau et al., 2017) made extensive movements, traveling directionally >100km/day for several days at a time, and regularly displaced thousands of km within the breeding area, between Reunion and Madagascar, Madagascar and the East African mainland, and along the Madagascar and East African coasts. This is in contrast to the 13 tagged ASHW that remained primarily in the coastal waters of Oman; the exception being the female individual M that transited across the Arabian Sea and back, exhibiting movement behavior that was an outlier in our ASHW sample, and more similar to typical behaviors observed in the southwest Indian Ocean. Since the ASHWs were also tagged during the early and mid- Northern Hemisphere breeding period, the contrast in behavior is likely related to the hypothesized year-round influence of prey availability on their movements. This further emphasizes the ecological distinctiveness of ASHW compared to other humpback whale populations.

4.2 Switching between shelf and deep-water habitats

Horizontal movements of whales in our study demonstrated that individuals switched behavior modes as they moved between shelf (<200m) and deeper water (>200m) habitats. The area restricted search behavior mode was dominant in the core home range in the shallow shelf waters of the Gulf of Masirah, an area where both foraging and breeding-related behaviors of ASHW have been documented (Mikhalev, 1997; Minton et al., 2011; Baldwin et al., 2011; Willson et al., 2012; Cerchio et al., 2016b; Willson et al., 2015, Willson et al., 2018). Whale movements in the Gulf of Masirah coincide spatially and seasonally with peak production from Oman’s most productive sardine fishery (Ministry of Agriculture and Fisheries Wealth, 2018).

The deeper dives in area restricted search mode were strongly associated with escarpment and canyon features. Navigation, opportunistic feeding, communication and competitive interaction with conspecifics have been proposed as hypotheses for the deep diving behavior for humpback whales in the south Pacific (Derville et al., 2020). However, the association of humpback whales and other rorquals with escarpment and canyon features has also been linked to the flow of nutrients up and down canyons that support increased prey density (Moors-Murphy, 2014). Baleen whales prefer foraging in areas where prey aggregations are most dense (Dolphin, 1987; Piatt and Methven, 1992; Baumgartner et al., 2003; Witteveen et al., 2008; Hazen et al., 2009, Goldbogen et al., 2008). The locations of deep dives (>100 m) along slope areas (such as those off Masirah Island) correspond to an area of the Arabian Sea where the seasonal presence of the relatively shallow oxygen minimum zone is associated with increased productivity in artisanal fisheries (Piontkovski and Claereboudt, 2012).

Soviet whaling revealed that both sardines and euphausiids were present in the stomachs of humpback whales taken in the Arabian Sea during November (Mikhalev, 1997). This plasticity in prey switching is consistent with other evidence documenting opportunistic foraging for this species (Baker et al., 1986, Payne et al., 1986, Clapham et al., 1997; Fleming et al., 2016). Our telemetry data raise questions about the relative contributions of deep water and shallow water foraging habitats to the nutritional requirements of ASHW and contribute to the understanding of oceanographic processes that provide suitable foraging conditions.

The extended tag duration from individual N also highlighted the potential importance of areas further away from the Gulf of Masirah such as the coastal waters of eastern Yemen, where this individual engaged in area restricted search behavior and deeper dives. High densities of euphausiids in plankton trawls have been reported from this area during the southwest monsoon (Hitchcock et al., 2002; Sutton and Beckley, 2017) and the presence of this individual in the area for a relatively extensive period of time suggests that the coast of eastern Yemen may be an important habitat for ASHWs.

The permanent residency of ASHW in the Arabian Sea coupled with year-round feeding events raises further questions about how the potentially unique income-breeding trait of this population is supported by a region characterized by seasonal upwelling coastal ecosystems (Reeves et al., 1991; Papastavrou and Van Waerebeek, 1997; Mikhalev, 2000; Minton et al., 2011; Pomilla et al., 2014). Whilst the telemetry data from this study does not directly provide evidence of feeding events, they demonstrate movements of individuals along pathways coincident with habitats known to be productive for humpback whale prey species based on evidence from fisheries data. Additional work is required to better define foraging areas and understand how such areas support the energetic requirements of ASHW throughout the year.

4.3 Long-range longitudinal movements

Long-range movements are represented by just one whale in our study (individual M), with others demonstrating restricted ranges albeit with limited durations of less than two months for the majority. Individual M’s movements of over an estimated 5,000 km provides the first direct evidence of travel across the Arabian Sea. This record represents persistent directional movement over a long distance and the precision-based navigation described in other humpback whale telemetry studies (Horton et al., 2011, Horton et al., 2017, Horton et al., 2020). Long-distance transiting behavior between important habitats, characterized by longer duration residency times and area restricted search behavior, are consistent with migratory movements described by satellite telemetry studies in other populations (Dulau et al., 2017; Andrews-Goff et al., 2018; Bedriñana-Romano et al., 2022). Acoustic studies have identified continuity in ASHW song structure from records compared between Oman and the west coast of India and Sri Lanka (Cerchio et al., 2018), and photographic identification work provided one capture of an animal sighted off the coast of Oman (Masirah) and India (Goa) (Minton et al., 2022). Together the data presents the possibility that some animals in the population are engaged in a form of seasonal migratory behavior within a relatively narrow latitudinal band.

The tracking record from individual M provides insights into the likely breeding and feeding related ecological drivers behind the movements. When individual M was tagged, she was the focal female in a competitive group in the Gulf of Masirah. Transiting movements off the coast of Goa, India passed within 30 km of areas where humpback whale song has been recorded and reported (Mahanty, 2015, Sutaria, 2018; Madhusudhana et al., 2019; Anderson et al., 2022). The animal’s month-long presence marked by area restricted search behavior off Kanyakumari coincides with an area known for high productivity and adjacent to an area where whales have been historically sighted (Wray and Martin, 1980; De Silva, 2000). Humpback whale song has also been documented on the Sri Lankan side of the Gulf of Mannar (Whitehead, 1985) and bubble-net feeding was observed in the first week of July 2020 off the town of Kalpatiya, Sri Lanka (R. Nanayakkara, personal communication to A.Willson 10^th July 2020). Individual M’s return to Omani waters at the end of March coincides with the end of the ASHW breeding season. Therefor the primary driver behind this cross-basin movement is less likely to be related to finding or avoiding mates and more closely related to foraging requirements due to increasing productivity associated with upwelling in the western Arabian Sea during the boreal summer (Hitchcock et al., 2002). Drivers for a gravid female to move towards specific calving and nursery habitat, if they exist for this population, would not be expected until before the start of the calving season in December (Mikhalev, 1997).

Further investigation is required to determine the extent of long-range movements and how they relate to foraging and breeding drivers across the Arabian Sea. A key uncertainty related to movements also includes the location of preferred calving or nursery grounds. Given the low encounter rates with mother-calf pairs in the Arabian Sea, current evidence for these areas, specifically Hallaniyat Bay and the Gulf of Masirah, remains largely circumstantial, based primarily on the high frequency of overall whale sightings and singing males during the breeding season and the location of the limited number of sightings (Minton et al., 2011; Cerchio et al., 2016b).

4.4 Study constraints

The tagging efforts completed in Oman aimed to instrument up to 20% of the population, which would be 12–22 animals based on the published population abundance estimate (n=82, 95% CI; 60-111; Minton et al., 2008). Six tags failed to successfully implant given shallow penetration of the tag due to the imperfect angle of the tag when striking the whale and/or the necessary pressure used in the ARTS being underestimated during the first ASHW tagging survey.

Our tagging efforts provided us with 13 individuals that contributed useful data but the dataset has a bias of nine known males and two known females (with two whales of unknown sex). Combined photographic identification and genetic studies have previously revealed an equal ratio of males to females sampled in the Gulf of Masirah, but a skew toward males in the Hallaniyat Bay (Minton et al., 2011). Tag sampling in this study was biased toward males when sampling in Dhofar, specifically by using hydrophones to locate singing individuals. The long-range movements of individual M indicate that it may be important to tag an increased proportion of females to gain better representation of the ecology and movements of ASHWs. In the southwest Indian Ocean, females tagged off Madagascar displayed significantly greater transiting behavior in SSSM analysis than males and tended to travel greater distances (Cerchio et al., 2016), a finding that is congruent with our singular observation in ASHW.

Temporal bias in the deployment of tags in November, late February and March, together with their limited longevity, resulted in a paucity of data for two periods: from late January to late February, and from June to October, with only one whale transmitting beyond June and into August. Given the hypothesized importance of the highly productive southeast monsoon period for foraging, it will be important to address this temporal sampling gap, although the collection of spatial information during this period, when weather conditions are typically inclement, has remained a challenge for both the telemetry and the vessel-based survey research approaches.

Tagging efforts were planned in areas of highest sighting density based on data from vessel-based surveys (Minton et al., 2011; Corkeron et al., 2011). This rationale was necessary to maximize the likelihood of locating and successfully tagging whales within limited deployment windows. Although results from home range analyses may carry some bias related to the tagging location, with eight of 14 functional tags deployed in the Gulf of Masirah, these results reveal genuine habitat preferences and site fidelity for this area, as five of the six individuals tagged in the Hallaniyat Bay moved into the Gulf of Masirah as well. This same high site fidelity has previously been documented by photo-identification studies (Minton et al., 2011; Willson et al., 2013). Whilst this manuscript identifies important ASHW habitat, it does not evaluate the environmental variables associated with them; these should be addressed in future research.

4.5 Vulnerabilities and management

The habitat switching of ASHW revealed by this study and foraging plasticity established by previous studies (Mikhalev, 1997) are likely to be driven by high variability in productivity based on the seasonal reversal of the monsoon systems that produce upwelling and downwelling events within the population’s range (Sutton and Beckley, 2017). The resilience and adaptability of ASHW to changes in prey distribution and density are also likely to be linked to prey tracking strategies, including the use of memory or proximate cues, as hypothesized for other baleen whales (Abrahms et al., 2019; Fagan, 2019). These strategies are potentially important traits for the population’s long-term survival, particularly in relation to anthropogenic threats across their range, and climate change.

The environmental divergence of factors influencing the productivity of sardines in the southeastern Arabian Sea together with their excessive capture has resulted in a situation described as a ‘biological catastrophe’ that is influencing the livelihoods of small-scale fishers in India (Kripa et al., 2018). Basin-scale decline of sardine landings was also documented off the coast of Oman based on data from the period between 2001 and 2011, a finding which has been linked to the shoaling of the oxygen minimum zone (Piontkovski and Al-Oufi, 2014). Denitrication and reduced oxygen concentration of surface waters in the Arabian Sea, caused by accelerated ecosystem changes linked to climate change, is also considered an emerging threat to the productivity of regional fisheries (Goes et al., 2020). To understand ASHW adaption to climate change, future studies should focus on ASHW foraging ecology through continued monitoring of ASHW body condition as an indicator of health status (Christiansen et al., 2020; Leslie et al., 2022) and the development of dynamic habitat use models (e.g. Hazen et al., 2017), supported by additional biotelemetry work. This could enable evaluation of the association between ASHW distribution, prey availability, reproductive success and fitness, as it has for North Atlantic right whales (Pendleton et al., 2012; Pershing and Pendleton, 2021).

The ability for ASHW to effectively use habitats, track prey and ultimately to recover from Soviet era whaling may also be influenced by complicating factors related to small populations. Interference with the cultural transmission processes, population connectivity and ‘adaption deficit’ (related to climate change) has previously been described for North Atlantic Right Whales (Whitehead et al., 2004; Brakes and Dall, 2016; Pendleton et al., 2012). Reduced connectivity within the population may also result in reduced genetic diversity and subsequent compromised immunity to disease or resilience to threats (Lacy, 1997; Bouzat, 2010; Pomilla et al., 2014). Recent population-level threats and shifts in oceanographic conditions have been hypothesized as the reason for range contraction of ASHW reported for the central Indian Ocean (Anderson et al., 2022). With our study documenting the geographical connectivity across the Arabian Sea from just one individual, further studies on ASHW movement throughout their range are also paramount, particularly to ensure that connectivity and population mixing is not impeded by anthropogenic activities (Dunn et al., 2019).

In addition to climate-change related threats to habitat suitability a number of other recognized acute anthropogengic threats are escalating within the ASHW range. Fisheries have been implicated in the mortality of over 4.1 million small cetaceans in the Indian Ocean between 1950 and 2018 (Anderson et al., 2020), and photo-based health assessments suggest that approximately two-thirds of ASHW display scarring attributable to fishing gear entanglements (Minton et al., 2022). A serious concern for ASHWs are gillnet based fishing methods which are documented as having a significant impact on marine mammals globally (Lewison et al., 2004; Jonsen et al., 2005; Read and Northridge, 2006, Reeves et al., 2013; Thomas et al., 2016) and are used prevalently in the Arabian Sea (FAO, 2013; Moazzam and Nawaz, 2014; Aranda, 2017). In addition, ship strikes, a known threat for large whales are also likely to be an issue within the home range of ASHW where cargo shipping traffic has increased by 35% over a 10 year period (Willson et al., 2016; Willson, 2021, Johnson et al., 2022). Our study reveals ASHW spent almost half of their time within 10 m of the surface, thus exposing animals to the threat of ship strike (McKenna et al., 2015), and entanglement from surface-set gillnet-based fishing methods.

4.6 Relevance to future conservation efforts

Results presented here, together with previous studies, strongly suggest that the Arabian Sea waters of Oman, and perhaps eastern Yemen, are a critical habitat for ASHW. The overlap of this isolated population with increasing shipping and fishing activities throughout its range, together with changes in prey availability from overfishing and climate change greatly limits the ability of ASHW to recover from previous depletion by Soviet whaling and to achieve and maintain a positive population trend into the future. Off southern Oman the overlap of coastal foraging areas with habitats associated with breeding further emphasizes the importance and value of protecting these areas. Whilst space-based solutions such as the creation of a network of managed, protected areas should be applied to connecting hot-spot areas critical for survival (such as in the Hallaniyat Bay and Gulf of Masirah), specific wide-scale threats should also be addressed with targeted threat-focused mitigation that may also cover corridors of longer range movements and the dynamic nature of whale distribution (Hooker et al., 2011; Hoyt, 2012; Di Sciara et al., 2016, Evans, 2018; Hazen et al., 2017; Johnson et al., 2022). The data derived from this study have previously been used to help delineate important marine mammal areas (IUCN MMPATF, 2019) and are currently being used to conduct detailed risk assessments to better understand the specific management measures that can be taken to reduce impacts associated with threats such as shipping and fisheries. Similar studies in Panama resulted in the designation of an IMO-endorsed Traffic Separation Scheme to minimize the risk of ship strikes in approaches to and from the Panama Canal (Guzman and Felix, 2017, Guzman et al., 2020).] This planning should take place at both national and regional scales, as the ASHW population is clearly transboundary. For example, recently identified habitat off the west and southern coasts of India now informs the development of population recovery plans (IWC, 2020) and government and industry stakeholders in Oman are working toward a national ASHW conservation plan (Environment Society of Oman and Environment Authority, 2023). The IWC and the Convention on the Conservation of Migratory Species of Wild Animals have endorsed a trans-boundary framework for conservation in the form of a joint regional Conservation Management Plan (IWC, 2011; Convention on Migratory Species, 2026). Whilst additional spatial ecology and risk assessments are required to address remaining knowledge gaps throughout ASHW range, it is of vital importance that efforts to develop management measures, especially within the home and core home ranges detailed in this study are immediately initiated to address known acute and chronic anthropogenic threats, to ensure population resilience and to facilitate the long-term survival, recovery and future trend of this population.

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