4.1 High-use area in Mauritius waters
Sperm whales disperse widely in all ocean basins and their global abundance estimate is in the hundreds of thousands (Whitehead 2002). Results from our limited sample size from a localized population in the Southwest Indian Ocean may not be representative of the behaviour of all sperm whales but fill a critical gap in our understanding of this deep diving species. The satellite tracked individuals highlighted two critical hotspots close to Mauritius as well as a migratory route between Mauritius and Rodrigues. Among the 21 sperm whales satellite tracked, 14 remained in close proximity to Mauritius up to a maximum of 107 days. The Mascarene islands (Reunion and Mauritius islands) have previously been identified as a suitable habitat for this species (Mannocci et al. 2014b), using aerial survey data. Here, satellite tracking data have allowed both resident and migratory movements of individually tracked whales to be described in this area and quantified. Although the time spent west of Mauritius varied across individuals, the kernel densities showed two clear hotspots located west and south-west of Mauritius. These two core areas might correspond to a breeding and a nursery ground during the wet and dry season, respectively. Despite mature males being observed from September to June in Mauritius waters, a larger proportion of mature males is seen between October and December in one of the highlighted core areas while more calves are mostly observed between March and April in the second one (M. Vely, unpublished data). The 16 months gestation period of this species (Ohsumi 1965) and a previous study showing that conception takes place in the austral summer south-east of South Africa (Findlay & Best 2016) together with observations of sperm whales giving birth in April (Gambell 1966) reinforce the importance of these potential breeding and nursery habitats in Mauritius waters.
4.2 Seasonal migratory patterns
Although the tracked sperm whales showed a strong site fidelity to Mauritius waters, a significant proportion of the individuals (40%) left the island’s coastal waters to perform a short migration towards Rodrigues during the wet season. These migrant whales were all mature females except one, and in 2018, 70% of the tracked whales showed a surprisingly synchronized departure from Mauritius in mid-December. These whales belong to two separate clans which are frequently observed interacting with each other (Sarano & Sarano 2017). Similarly to the Atlantic, the genetic structure in the Indian Ocean is mostly attributed to geographic philopatry (Alexander et al. 2016), which could partly explain the substantial difference observed between males and females in our study (Engelhaupt et al. 2009).
In addition to social connections, environmental drivers might also explain such a migratory behaviour. As the whales seemed to move into cooler areas, it is possible that an increase in temperature in Mauritius waters may have impacted them either directly, by affecting their physiology (i.e. capacity to dissipate excess heat), or indirectly by impacting the distribution of their prey. Unfortunately, direct data on prey distribution were not available for this region, and proxies of micronekton biomass via mid-trophic level models (e.g. SEAPODYM) did not show temporal differences that could explain the apparent abandonment of coastal areas near Mauritius. Given that female sperm whales generally congregate into large social groups (Best & Folkens 2007), their synchronized departure could also be related to their social structure and the contrasting behaviour between males and females. Sperm whales are considered to be income breeders (Oftedal 1997) and a behavioural dichotomy is generally observed between males and females. In an Australian sperm whale population, Irvine et al. (2017) have shown that the males are present all year round whereas the females are mostly seen between April-May and September-November, suggesting a migratory behaviour similar to the one found in our study. Although some tracked females did not seem to have left Mauritius, it could simply be due to the relatively short tracking duration for these whales. The limited sample size of this study reinforces the need to track more individuals over the entire annual cycle to clarify the distribution and seasonal patterns of this sperm whale population. Although the majority of the mature males tracked from Mauritius remained in close proximity to the island, suggesting a resident behaviour, several studies indicate that mature males move to higher latitudes before and after the breeding season (Mellinger et al. 2004, Wong & Whitehead 2014, Whitehead 2018). Accordingly, the only male that left Mauritius headed southward in a straight line. This male may have headed towards Crozet or Kerguelen Archipelagos, which are famous hotspots for this species where large males are regularly observed feeding on Patagonian toothfish from longliners (Tixier et al. 2019).
Even though sperm whales are occasionally found in coastal waters, they must be considered pelagic animals that forage on ephemeral prey resources over large ocean scales (Kawakami 1980). The variable location of their prey resources may translate into seasonal foraging movements to maintain fitness. But to date, little is known about what drives the movements of sperm whales. In particular, nothing is known about their feeding habits in the waters around Mauritius. Their restricted and sinuous movements close to the island however suggest that they are also feeding in these waters, likely on squid, their main prey resource (Kawakami 1980). In this study, the sperm whales conducted shallower dives at night, but did not seem to change the duration of their dives. Davis et al. (2007) studied diurnal vertical migrations of sperm whale and squid in the California Gulf and found that the whales followed the vertical excursions of squids in shallower depths during the night (Stewart et al. 2013), which is in agreement with the diel pattern found in our study. Squids are often considered to be sensitive to temperatures at depth and the vertical movement patterns of the sperm whales observed in this study may be in reaction to changes in squid diel vertical migration (Gilly et al. 2006). Although 11 tags were deployed to record dive data, unfortunately data from a few dives were transmitted, preventing comparison of the diving behaviour between seasons and between males and females. Deployment of acoustic tags with time depth recorders and 3D accelerometers could confirm if the sperm whales are feeding in this area.
4.3 Predicted distribution and its conservation implications
An important finding from this study is that even a small sample of tracked whales can provide new and important insight into the physical and oceanographic factors that drive the movements of this deep diving species. This is mainly thanks to the novel method used here to compare models for detecting habitat selection using 14 different supervised machine learning algorithms, and to generate site specific insight into sperm whales’ behaviour. Unlike the traditional regression methods commonly used in SDMs (e.g. GLM), the machine learning-based approach used in this study have the ability to model complex polynomial relationships without relying on unrealistic assumptions (e.g. linearity) (Thessen 2016). Using the ensemble approach, we also provide a new way to combine predictions from several algorithms, which is to date rarely used in spatial ecology. We therefore recommend to test a minimum of ten different algorithms when trying to predict animal’s distribution, in order to capture the more complex relationships between a species’ occurrence and its environment, and therefore increase the predictive power of the model to get the most reliable predictions despite limited sample sizes. Our results show a strong seasonal pattern with more dispersed movements during the wet season (Dec-Mar) and affinity to contrasting environmental predictors according to the season. Our best model during the wet season showed the strongest affinity for SSH, which is in agreement with a previous study that showed higher sperm whales densities in areas of higher Sea Level Anomalies (Mannocci et al. 2014b). This suggests that sperm whales are likely looking for enriched pelagic waters that could be associated with mesoscale features (i.e. eddies, fronts) when departing from Mauritius. However, we did not find any direct relationship between the whales’ tracks and eddies or fronts east of Mauritius during the wet season, probably due to the relatively low mesoscale activity in the Mascarene compared to the Mozambique Channel, where sperm whales encounter rates are much higher .(Mannocci et al. 2014b) During the dry season, the most important predictor was the bottom temperature followed by the bathymetry. This highlighted affinity for particular areas close to Mauritius that are likely associated with higher prey densities in colder waters at certain depths.
In our study, the habitat for sperm whales extended over a restricted latitudinal band (19.5-22°S), which contrasts with previous studies showing north-south migrations (Whitehead et al. 2008, Findlay & Best 2016). During the dry season, the predicted distribution was limited to coastal waters of Mauritius and Reunion islands, reinforcing the need to implement conservation measures in these areas, i.e. promote reserve designation, extend the actual MPAs. Currently, Mauritius has eight MPAs including two marine parks and six areas declared as fishing reserves. They are however relatively small (between 3.5-63.4 km²) and confined to areas close to shore (Francis et al. 2002). Data on animal distribution is often lacking when designing MPAs, and findings like ours are therefore essential to support conservation planning. Our results could also contribute to the regulation of the whale watching industry, which is omnipresent in such touristic areas. Restricting disturbance of animals is of particular importance at breeding sites like Mauritius coastal waters. Rather than static and sometimes inadequate MPAs, here we recommend designing dynamic MPAs based on the seasonal prediction maps of the whales (Maxwell et al. 2015). In addition to filling a gap in our knowledge about the movements and habitats of sperm whales in the South Western Indian Ocean, our study will contribute to the implementation of concrete conservation measures in the waters of Mauritius and Reunion by clearly delineating the breeding and foraging grounds of this vulnerable species. Our findings are of particular importance in the Indian Ocean, where regional assessments are still lacking despite the presence of sperm whales (Laran et al. 2017a, Huijser et al. 2020). Our results should therefore supplement existing sperm whale’s records available from international databases like the Global Biodiversity Information Facility (GBIF) to support regional assessments.