Satellite Tagging and Photographic Identification Reveal Connectivity Between Two UNESCO World Heritage Areas for Reef Manta Rays

Southward range extension and transboundary movements of reef manta rays Mobula alfredi along the east African coastline

Opportunistic in-water and aerial surveys in South Africa and the analysis of contributed citizen science data have extended the known range of reef manta rays Mobula alfredi along the eastern coast of Africa by 140 km (to Mdumbi Beach) and verified the first transboundary movements for the species. Additionally, six new long-range dispersal records have provided evidence of connectivity with the M. alfredi population off the Inhambane coastline of Mozambique. Five of these records captured one-way movements, the longest of which was an individual that travelled 505 km from Praia do Tofo to Sodwana Bay with 301 days between sightings. A single individual made a return trip between Závora, Mozambique and Sodwana Bay, South Africa (a total distance of ~870 km). These findings support the Convention on Migratory Species listing for the species, suggesting regional transboundary management units are warranted for this wide-ranging elasmobranch.

Evidence of Závora Bay as a critical site for reef manta rays, Mobula alfredi, in southern Mozambique

The largest known reef manta ray (Mobula alfredi) population in Africa has been monitored for more than 20 years at several locations on the coast of the Inhambane Province in southern Mozambique. Nonetheless, before this study, little had been reported on the population dynamics of M. alfredi from Závora, a remote bay in the region. Photographic mark-recapture was used to investigate the size and structure of M. alfredi that aggregate at "Red Sands," a reef cleaning station in Závora Bay. An 11 year photographic data set was used to identify 583 M. alfredi individuals between 2010 and 2021. More than half of M. alfredi individuals were resighted at least once, with most encounters (up to 18 for one individual) occurring during the peak sighting period in July-November each year. An even sex ratio was observed, 44% females and 50% males, with no significant difference in resightings between the sexes. Pollock's robust design population models were used to estimate annual abundance, emigration, annual apparent survival and capture probability at Red Sands from July to November over a 6 year period (2016-2021). Abundance estimates varied year to year, ranging from 35 (95% c.i. [30, 45]) up to 233 (95% c.i. [224, 249]) M. alfredi individuals. Given the seasonal affinity of M. alfredi observed at Red Sands, this study highlights the importance of understanding fine-scale site use within the larger home range of this population to develop local management strategies.

The role of context in elucidating drivers of animal movement

Despite its consequences for ecological processes and population dynamics, intra-specific variability is frequently overlooked in animal movement studies. Consequently, the necessary resolution to reveal drivers of individual movement decisions is often lost as animal movement data are aggregated to infer average or population patterns. Thus, an empirical understanding of why a given movement pattern occurs remains patchy for many taxa, especially in marine systems. Nonetheless, movement is often rationalized as being driven by basic life history requirements, such as acquiring energy (feeding), reproduction, predator-avoidance, and remaining in suitable environmental conditions. However, these life history requirements are central to every individual within a species and thus do not sufficiently account for the high intra-specific variability in movement behavior and hence fail to fully explain the occurrence of multiple movement strategies within a species. Animal movement appears highly context dependent as, for example, within the same location, the behavior of both resident and migratory individuals is driven by life history requirements, such as feeding or reproduction, however different movement strategies are utilized to fulfill them. A systematic taxa-wide approach that, instead of averaging population patterns, incorporates and utilizes intra-specific variability to enable predictions as to which movement patterns can be expected under a certain context, is needed. Here, we use intra-specific variability in elasmobranchs as a case study to introduce a stepwise approach for studying animal movement drivers that is based on a context-dependence framework. We examine relevant literature to illustrate how this context-focused approach can aid in reliably identifying drivers of a specific movement pattern. Ultimately, incorporating behavioral variability in the study of movement drivers can assist in making predictions about behavioral responses to environmental change, overcoming tagging biases, and establishing more efficient conservation measures.

Home sweet home: spatiotemporal distribution and site fidelity of the reef manta ray (Mobula alfredi) in Dungonab Bay, Sudan

BACKGROUND

Reef manta ray (Mobula alfredi) populations along the Northeastern African coastline are poorly studied. Identifying critical habitats for this species is essential for future research and conservation efforts. Dungonab Bay and Mukkawar Island National Park (DMNP), a component of a UNESCO World Heritage Site in Sudan, hosts the largest known M. alfredi aggregation in the Red Sea.

METHODS

A total of 19 individuals were tagged using surgically implanted acoustic tags and tracked within DMNP on an array of 15 strategically placed acoustic receivers in addition to two offshore receivers. Two of these acoustically monitored M. alfredi were also equipped with satellite linked archival tags and one individual was fitted with a satellite transmitting tag. Together, these data are used to describe approximately two years of residency and seasonal shifts in habitat use.

RESULTS

Tagged individuals were detected within the array on 96% of monitored days and recorded an average residence index of 0.39 across all receivers. Detections were recorded throughout the year, though some individuals were absent from the receiver array for weeks or months at a time, and generalized additive mixed models showed a clear seasonal pattern in presence with the highest probabilities of detection occurring in boreal fall. The models indicated that M. alfredi presence was highly correlated with increasing chlorophyll-a levels and weakly correlated with the full moon. Modeled biological factors, including sex and wingspan, had no influence on animal presence. Despite the high residency suggested by acoustic telemetry, satellite tag data and offshore acoustic detections in Sanganeb Atoll and Suedi Pass recorded individuals moving up to 125 km from the Bay. However, all these individuals were subsequently detected in the Bay, suggesting a strong degree of site fidelity at this location.

CONCLUSIONS

The current study adds to growing evidence that M. alfredi are highly resident and site-attached to coastal bays and lagoons but display seasonal shifts in habitat use that are likely driven by resource availability. This information can be used to assist in managing and supporting sustainable ecotourism within the DMNP, part of a recently designated UNESCO World Heritage Site.

Using Drones to Assess Volitional Swimming Kinematics of Manta Ray Behaviors in the Wild

Drones have become increasingly popular tools to study marine megafauna but are underutilized in batoid research. We used drones to collect video data of manta ray (Mobula cf. birostris) swimming and assessed behavior-specific kinematics in Kinovea, a semi-automated point-tracking software. We describe a ‘resting’ behavior of mantas making use of strong currents in man-made inlets in addition to known ‘traveling’ and ‘feeding’ behaviors. No significant differences were found between the swimming speed of traveling and feeding behaviors, although feeding mantas had a significantly higher wingbeat frequency than traveling mantas. Resting mantas swam at a significantly slower speed and wingbeat frequency, suggesting that they were continuously swimming with the minimum effort required to maintain position and buoyancy. Swimming speed and wingbeat frequency of traveling and feeding behaviors overlapped, which could point to other factors such as prey availability and a transitional behavior, influencing how manta rays swim. These baseline swimming kinematic data have valuable applications to other emerging technologies in manta ray research.