Investigating the predation risk of coastal dolphins via the presence of shark bite scars across south-east Queensland, Australia

Investigating the predation risk of coastal dolphins via the presence of shark bite scars across south-east Queensland, Australia | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 9 January 2026 V1 Latest version Share on Investigating the predation risk of coastal dolphins via the presence of shark bite scars across south-east Queensland, Australia Authors : Georgina Hume 0000-0002-8690-6721 [email protected] , Alexis Levengood , Gemma Webster , Kathy Townsend , Victor Peddermors , and Bonnie Holmes Authors Info & Affiliations https://doi.org/10.22541/au.176796374.46067537/v1 376 views 188 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract \articletype Original Articles Predation and its risk influence the ecology and evolution of both predator and prey species. Despite this, predatory attempts of large apex sharks on cetaceans often go unseen, constraining empirical assessments of their frequency and ecological significance. Shark bite scars can be used as an indirect measure to quantify predation risk on dolphins and may reveal species-specific and spatial patterns of predator-prey interactions. Here, we analysed photographs of coastal dolphins in south-east Queensland, Australia to compare predation risk between multiple dolphin species across differing habitats. Using fresh wounds, bites were mainly attributed to tiger (Galeocerdo cuvier) and white (Carcharodon carcharias) sharks, with the peduncle being the most bitten body region across all species. Shark bite scarring differed between species: 50.3% of Australian humpback (Sousa sahulensis), 27.7% of Indo-Pacific bottlenose (Tursiops aduncus) and 38.5% of common bottlenose (Tursiops truncatus) exhibited scars. Dolphins had more scars in sheltered waters (42.6%) compared to open waters (16.3%). Generalised linear models confirmed S. sahulensis were more susceptible to predation attempts, with non-calves in sheltered waters most at risk. These findings provide a baseline for current predation risk across multiple habitats of sympatric dolphin species in Queensland, providing insight into drivers of the predator-prey interactions. \articletype Original Articles Investigating the predation risk of coastal dolphins via the presence of shark bite scars across south-east Queensland, Australia Georgina V. Hume 1,2 , Alexis L. Levengood 1,2 , Gemma L. Webster 1,2 , Kathy A. Townsend 1,2 , Victor M. Peddemors 3 and Bonnie J. Holmes 1,2 \articletype Original Articles 1 School of Science, Technology & Engineering, University of the Sunshine Coast, Queensland, Australia \articletype Original Articles 2 Marine and Terrestrial Megafauna Research Cluster, University of the Sunshine Coast, Sippy Downs, Queensland, Australia 3 New South Wales Department of Primary Industries & Regional Development, Sydney Institute of Marine Science, Mosman, New South Wales, Australia \articletype Original Articles Correspondence Georgina V. Hume, School of Science, Technology & Engineering, University of the Sunshine Coast, Sippy Downs, QLD, 4556, Australia. Email: [email protected] \articletype Original Articles Abstract (200 words) Predation and its risk influence the ecology and evolution of both predator and prey species. Despite this, predatory attempts of large apex sharks on cetaceans often go unseen, constraining empirical assessments of their frequency and ecological significance. Shark bite scars can be used as an indirect measure to quantify predation risk on dolphins and may reveal species-specific and spatial patterns of predator-prey interactions. Here, we analysed photographs of coastal dolphins in south-east Queensland, Australia to compare predation risk between multiple dolphin species across differing habitats. Using fresh wounds, bites were mainly attributed to tiger ( Galeocerdo cuvier ) and white ( Carcharodon carcharias ) sharks, with the peduncle being the most bitten body region across all species. Shark bite scarring differed between species: 50.3% of Australian humpback ( Sousa sahulensis ), 27.7% of Indo-Pacific bottlenose ( Tursiops aduncus ) and 38.5% of common bottlenose ( Tursiops truncatus ) exhibited scars. Dolphins had more scars in sheltered waters (42.6%) compared to open waters (16.3%). Generalised linear models confirmed S. sahulensis were more susceptible to predation attempts, with non-calves in sheltered waters most at risk. These findings provide a baseline for current predation risk across multiple habitats of sympatric dolphin species in Queensland, providing insight into drivers of the predator-prey interactions. KEYWORDS Sousa sahulensis , Tursiops aduncus , shark-inflicted injuries, predator-prey interactions, predator avoidance. 1 | INTRODUCTION Predation risk is a critical driver in ecology and can help shape the distribution, group size, group competition and habitat use of prey species (Fryxell et al. , 2007, Lima and Dill, 1990, Norris and Schilt, 1988, Wirsing et al. , 2008). However, depending on the probability of predator-prey interactions, the relative importance of predation risk varies between species, habitats and populations (Heithaus and Dill, 2006, Labra and Niemeyer, 2004). Although often considered top predators, small cetaceans are still at risk of predation from both large sharks and orcas ( Orcinus orca ), particularly in waters where the range of these predatory species overlaps (Heithaus, 2001b, Weller, 2009). Predation risk for small cetaceans in temperate waters tends to originate from orcas, whereas tropical ecosystems are dominated by sharks (Weller, 2009). These threats have been demonstrated to influence delphinid movement, behaviour and overall habitat use (Connor and Heithaus, 1996, Heithaus and Dill, 2002). Despite general knowledge regarding predators, for many small cetacean populations there is currently no information on predation risk. Identification of predation risk, rate, and how it shapes dolphin movements is vital to our understanding of how it might drive cetacean behaviours and population dynamics. These drivers have the ability to influence dolphin prevalence in time and space, and are important precursors to understanding their broader ecology (Heithaus and Dill, 2002). In tropical and sub-tropical waters, large sharks play an important role in regulating the food web, predating on sick, injured and vulnerable species, including small cetaceans (Heithaus and Dill, 2002, Kiszka et al. , 2015, Wirsing et al. , 2008). Species such as bull ( Carcharhinus leucas ), tiger ( Galeocerdo cuvier ) and white ( Carcharodon carcharias ) sharks all undergo ontogenetic dietary shifts as they grow, expanding their diet from smaller fishes and crustaceans to include other elasmobranchs, turtles, and marine mammals like dugongs and delphinids (Grainger et al. , 2020, Heithaus, 2001a, Kim et al. , 2012, Malcolm et al. , 2001, Salinas-de-León et al. , 2019, Türtscher et al. , 2022). These shifts are intrinsically linked to increasing energetic requirements in relation to sexual maturity, along with physiological changes in jaw gape and tooth morphology (Ferrara et al. , 2011, French et al. , 2017, Goodman et al. , 2022, Holmes et al. , 2015). Dolphin blubber constitutes a rich food source, and therefore the hunting strategies employed by larger sharks may involve attempts at singular bites, compared to riskier lethal attacks on cetaceans that can also inflict injuries to the shark during capture (Heithaus, 2001b). Due to the high levels of fat in the blubber, a single bite may provide substantial energetic gain to larger sharks, while minimising the energetic expenditure needed to exhibit a full lethal attack on a dolphin (Heithaus, 2001b). In the presence of predatory sharks, dolphins have been shown to move to deeper, more open waters (Heithaus and Dill, 2002, Sprogis et al. , 2018), spend time in larger groups in shallower waters (Heithaus and Dill, 2002), increase their speed when travelling, and undertake increases in leap frequency to avoid potential attack (Connor and Heithaus, 1996). These predator-prey dynamics may shape habitat preference for where the dolphins choose to rest and forage, as habitat selection reflects trade-offs between resource availability and increased predation risk. Shark bites are distinguished from other markings as they are typically crescent shaped, jagged and have widely spaced tooth marks (Heithaus, 2001a). Dolphins exhibit a relatively fast healing process (1-6 months) (Corkeron et al. , 1987b, Orams and Deakin, 1997), therefore, once the bite is fully healed, species identification and size estimates of the shark responsible are difficult to distinguish as the characteristics (i.e., tooth spacing) of the bite become harder to determine (Smith et al. , 2018). There have been only a few studies where shark bite species identification has been achieved. For example, in the tropical Kimberly region of northwestern Australia, G. cuvier bites were the most prevalent across three coastal dolphin species (Smith et al. , 2018), while in Moreton Bay, Queensland, Australia, predation attempts on dolphins were attributed to both G. cuvier and C. carcharias (Corkeron, 1987). These regional differences highlight the importance in identifying which shark species prey upon dolphins to assess spatial variation in predation risk and differences in predator-prey dynamics. One of the challenges that comes with quantifying shark predation risk is successful shark predatory events are rarely observed in the wild (e.g., Sucunza et al. (2015)). More recently, through advancements in genomic approaches, studies have been able to use environmental DNA (eDNA) metabarcoding from cloacal swabs of sharks to confirm marine mammal predation (Clark et al. , 2023), an advancement on traditional stomach content analyses (Cockcroft, 1989, Grainger et al. , 2020, Heithaus et al. , 2017). However, the use of both stomach contents and eDNA analyses does not provide a complete overview of the predation risk to dolphins, as it does not account for the failed predation attempts (Heithaus, 2001a). These failed shark predation attempts, commonly seen on dolphins as visual bite scars and wounds, can be used to infer predation risk and rate to dolphins (Heithaus, 2001a, Heithaus and Dill, 2006). In the absence of shark specimens (stomach contents or cloacal swab availability), when trying to recognise the predation risks within- and between- dolphin populations, the presence, absence, frequency and any trends of these wounds and scars can be quantified to understand predation risk (Heithaus, 2001a). As such, bite wounds can serve as a proxy for predation risk and can then be used to infer how this risk might be driving dolphin population dynamics such as habitat selection, behavioural state and group size. The frequency of shark bites has been shown to vary between dolphin species, habitats and years. For example, in a resident population of common bottlenose dolphins ( Tursiops truncatus ) in Sarasota Bay, Florida, shark bite frequency increased to 35.5% in 2015 (Wilkinson et al. , 2017) from 22% between 1975-1985 (Wells, 1991, Wells et al. , 1987). In northwestern Australia, Smith et al. (2018) reported 72% of Australian snubfin dolphins ( Orcaella heinsohni ) displayed evidence of shark predation attempts, compared to 46% of Australian humpback dolphins ( Sousa sahulensis ) and 18% of Indo-Pacific bottlenose dolphins ( Tursiops aduncus ) in the same region. The only habitat comparison of shark bite scarring on live animals was reported by Sprogis et al. (2018), noting the proportion of shark bites was higher in dolphins that resided in sheltered waters compared to those in open waters. These are all examples of why greater understanding of how local environmental factors, coupled with seasonal shark movements, are needed to determine the predation risk for each dolphin population. Only then can the predator-prey dynamics of a region and the subsequent influences that this may have on dolphin behaviour, ecology and habitat be better understood at both a temporal and spatial scale. However, there remains a paucity of quantified predation risk for many dolphin populations. Baseline assessments are particularly critical in densely populated coastal regions, where dolphins have cumulative pressures from both natural threats (i.e., predation) and anthropogenic pressures such as pollution, habitat loss and vessel traffic (Pirotta et al. , 2013, Pirotta et al. , 2015). Understanding baseline predation risk in these areas is essential for monitoring changes, as anthropogenic disturbances may alter dolphin behaviour and habitat use leading to increased susceptibility in predation risk. In this study, we used photographic evidence to investigate the natural threat to dolphins present in south-east Queensland (hereafter ‘SEQ’) (inclusive of the Sunshine Coast and the Great Sandy Marine Park, hereafter ‘GSMP’) via the presence of shark bite scarring. There remains a paucity of information on the natural threats of dolphins in SEQ outside Moreton Bay (Corkeron et al. , 1987a, Hawkins et al. , 2022), and how these threats impact dolphin behaviour and ecology. Therefore, we assessed predation attempts on dolphins commonly found in SEQ ( Delphinus delphis , O. heinsohni, S. sahulensis , T. aduncus and T. truncatus ) to; 1) identify which shark species were responsible for predation attempts; 2) assess if there were differences in the distribution of bites on the body area; 3) determine if unsuccessful shark predation attempts differs by dolphin species, habitat type, age class, group size and depth; and 4) investigate if the number of bites per individual differed between species and habitat type. 2 | METHODS 2.1 | Study area Data were collected year-round in SEQ, Australia in the GSMP (25.35 o S, 152.95 o E) inclusive of Hervey Bay, the Great Sandy Straits and Tin Can Inlet (Butchulla Country), and along the coastal waters of the Sunshine Coast from Noosa to Caloundra (Gubbi Gubi/Kabi Kabi Country, 26.55 o S, 153.12 o E) (Figure 1). The area surveyed in the marine park was ~2,800 km 2 , whereas, to keep habitat features comparable (i.e., depth limits) the Sunshine Coast survey area was smaller, consisting of ~350 km 2 of coastal (< 3 nm) and offshore waters (up to 10 nm). ‘Open’ waters hereafter consist of the ‘Sunshine Coast’ waters, comprising unprotected sandy beaches, small embayment’s, rocky headlands and river access points. These waters are frequently subjected to large swell from the Pacific Ocean and feature a sloping bottom that reached a maximum depth of 31.9 m within the sampled area. Conversely, ‘sheltered’ waters of the GSMP are not subjected to this consistent swell, being protected and constrained by mainland Australia on the west, and the sand island K’gari (Fraser Island) to the east. The bay contains shallow coral reefs, intertidal wetlands, mudflats, seagrass beds, shifting sandbars, a number of estuaries and rivers flowing into the system and a mean water depth of 15 m (Gräwe et al. , 2009). 2.2 | Data collection Data was collected as part of a larger project investigating dolphin connectivity in SEQ. Opportunistic, boat-based surveys occurred between 2022-2025 using a 5.5 m vessel with a Yamaha 115 hp outboard motor. Individual dolphins were photographed using a Nikon D7500 DSLR camera with a 100-400 mm telephoto zoom lens. Upon encountering a dolphin or group, the following data were collected: dolphin species, individual ID (if known), sex, location (via GPS), water depth, sea state, water temperature, group size, behavioural state and life history information (e.g., age-class, reproductive status). Sex was determined by views of the genital area (when possible) or by consistent association with a calf (Mann et al. , 2000, Smolker et al. , 1992). Age-class was defined as: calf (i.e., individual was < 2/3 of an adult size and frequently found in echelon or infant position with an adult, presumably the mother) or non-calf (consisting of juveniles, sub-adults, and adults) (Whitehead and Mann, 2000), as exact ages are not known for most of the population. A group was defined as all individuals within 10 m of another (Smolker et al. , 1992). 2.3 | Data selection Individual dolphins were identified using standard dorsal fin photo-identification methods including the shape, scars, nicks, wounds and pigmentation (Würsig and Würsig, 1977) using photographs collected between 2022-2025. Photographs were graded from A (i.e., best quality) to F (i.e., not usable) as part of the photo-identification process; photographs that were scored A-C only were used for this study (Würsig and Jefferson, 1990). Only dolphins that were able to be individually identified were included; this ensured shark bites weren’t being documented multiple times when individuals were resighted on different days. For shark bite identification, photographs were inspected on the following body areas: the head, anterior, dorsal fin, mid-flank and peduncle (as described in Scott et al. (2005), Figure 2). These body areas were chosen as they are the most readily photographed when a dolphin surfaces. All individually identifiable dolphins were included in the descriptive results to allow for a broad overview between species across SEQ. However, to ensure scar presence was not biased towards individuals with greater photographic coverage, only individuals that had been photographed on both sides were included in the final subset that was subsequently used for statistical analysis (Heithaus, 2001b, Smith et al. , 2018). As such, D. delphis ( n = 21) and O. heinsohni ( n = 1) were removed from statistical analysis due to insufficient sample sizes. T. truncatus could only be included in the region-wide analysis as they also had insufficient sample size for habitat specific analysis. This resulted in a total of 720 individual dolphins for the descriptive results and 564 individuals for the final subset used in statistical analysis. 2.4 | Shark bite analysis All individuals in the photo-identification catalogue were assessed visually for evidence of shark bites. Shark bites differ from other marks attributed to dolphins or other species (e.g., bird rakes) as they are typically jagged, have a crescent shape and are made of widely spaced tooth marks (Heithaus, 2001a). Marks that are narrowly spaced or shallow tend to be from other dolphin interactions (Scott et al. , 2005). Linear scars (sometimes attributable to plunging birds in a mixed species foraging event (Kügler and Orbach, 2014)) and small notches on any body part were not included due to uncertainty of their origin. Each shark bite was assigned to the body area it mostly covered (>50% of the scar) (‘L’ = left side, ‘D’ = dorsal side, ‘R’ = right side, ‘V’ = ventral side) and the healing classification (adapted from (Smith et al. , 2018, Sprogis et al. , 2018)) of the scar was assigned (open ‘O’ = wound from the last two months, including broken skin with some blubber, blood or muscle shown; intermediate ‘I’ = wound is 2-6 months old and shows some healing, white scarring will be seen; healed ‘H’ = wound is more than six months old and is completely healed; Figure 3). 2.4.1 | Shark bite species identification Some shark bites can be identified to the species-level based on the bite characteristics (Corkeron, 1987). For example, G. cuvier have a wide head with teeth that are large and widely spaced, inflicting a slashing bite (Clua et al. , 2023, Heithaus, 2001a). Although both C. carcharias and C. leucas both have triangular serrated teeth on their upper jaws, the interdental distance ‘IDD’, (i.e., the distance between adjacent tooth tips (Lowry et al. , 2009)) relative to the jaw circumference or bite width differs between the two; C. carcharias exhibits larger IDD compared to C. leucas which has overlapping upper jaw teeth (Clua and Reid, 2018). Similarly, lower jaw bite imprints can be differentiated based on bite characteristics; C. carcharias exhibits a less ragged appearance than C. leucas due to the former possessing serrated triangular lower jaw cutting teeth (Hunt et al., in press) compared to the non-serrated tearing teeth of C. leucas (Goodman et al. , 2022). However, difficulties in shark species identification occur when associated with old or partially visible (i.e., the mark from the lower jaw was underwater) wounds (Heithaus, 2001b, Smith et al. , 2018). As such, identification of the shark species responsible for bites was only attempted on the open and intermediate bites by two experienced shark biologists (VMP and BJH) looking for species-specific distinctive features in the bite wounds. 2.4.2 Data analysis All data were analysed in R version 4.4.3 (R Core Team, 2024). To investigate if shark bite presence differed between dolphin species and habitat type, chi-squared tests (χ 2 ) with Bonferroni correction (alpha = 0.025) were used. For each dolphin, the average depth and average group size were calculated based on the total number of sightings. These values were then included in the models outlined below. Binomial generalised linear models (GLMs) were run to investigate drivers of shark bite presence on the dolphins. Dolphin species, age class, habitat type, average group size, average depth and interactions between these predictors were included as possible explanatory variables. To investigate the drivers of the number of bites per individual, Poisson GLMs were run with the same possible explanatory variables. Sex was not included in the analyses due to inconsistencies in being able to confidently and consistently identify sex without error. The dredge function from the MuMIn package (Bartoń, 2022) was used for both the shark bite presence and the shark bite number models to generate model selection tables with all possible combinations (subsets) of fixed terms for each global model and to determine the optimal model by selecting the model with the lowest AICc. Models within Δ AICc <2 were considered competitive (Table S1). Finally, to investigate species differences in where bites occurred on the body area; body specific heat maps were created for the most prevalent species ( S. sahulensis and T. aduncus ), and Fisher’s Exact tests were run to statistically test for body area differences. 3 | RESULTS Between 2022-2025, 166 survey days were completed, totalling 599 dolphin surveys across the region. This resulted in six D. delphis sightings, one O. heinsohni sighting, 173 S. sahulensis sightings, 382 T. aduncus sightings, 21 T. truncatus sightings and 16 sightings where species identification could not be determined due to brevity in sighting/loss of individuals. From these surveys, a total of 720 individually identifiable dolphins were catalogued, 207 S. sahulensis ; 472 T. aduncus , 19 T. truncatus , 21 D. delphis, and one O. heinsohni. Individuals were sighted an average of 2.81 ± 2.16 times (range 1-13) and group sizes ranged from one to ~50 individuals (average 10.96 ± 8.56). A total of 338 shark bites were identified on 231 of the 720 dolphins, resulting in 32% of the SEQ dolphin population surviving predation attempts. The presence of shark bite scars differed between species ( D. delphis (4.8%, n = 21), O. heinsohni (100%, n = 1), S. sahulensis (48.3%, n = 209), T. aduncus (26.0%, n = 470), T. truncatus (31.6%, n = 19)). The presence of bites was higher for all species in sheltered compared to open water habitats (Figure 4). These bites were categorised as Open ( n = 22, 6.5%), Intermediate ( n = 46, 13.6%) and Healed ( n = 270, 79.9%) wounds (Table 1). The peduncle was the most bitten body region ( n = 171, 50.6%), followed by anterior ( n = 78, 23.1%), mid-flank ( n = 68, 20.1%), dorsal ( n = 15, 4.4%), and the head ( n = 6, 1.8%) (Table 1). 3.1 | Shark species identification Shark species identification was possible for 15 of 22 open and intermediate bites based off tooth spacing and bite characteristics. Four species/genera of sharks were characterised as the suspected predators. The most common species responsible for shark bites were G. cuvier and C. carcharias ( n = 6, Table 2). Bites from C. leucas were only attributed to S. sahulensis (Table 2). 3.2 | Distribution of shark bites by body area There was no significant difference between bites on the left and right sides of individuals exhibiting shark-bite scarring ( S. sahulensis: χ 2 = 0.78, df = 1, p = 0.38 ; T. aduncus : χ 2 = 1.05, df = 1, p = 0.31), therefore, sides were not included in analysis. The distribution of scarring across the body region of S. sahulensis was not random ( p < 0.001) with most shark bites occurring in the peduncle region (42.5%), followed by the anterior (30.6%), mid-flank (21.9%), dorsal (3.1%) and head (1.9%) (Figure 5a). The distribution of scarring across the body region of T. aduncus was also not random ( p < 0.001) with most shark bites occurring on the peduncle region (55.6%), followed by the mid-flank (21.8%), anterior (15.8%), dorsal (5.3%) and head (1.5%) (Figure 5b) 3.3.1 | Variation in shark bite presence between species and habitat type After filtering for the subset of individuals that included photographs of both sides, the presence of shark bite scarring significantly differed between species for the SEQ region ( S. sahulensis = 50.3%, n = 179; T. aduncus = 27.7%, n = 372; T. truncatus = 38.5%, n = 13; χ 2 = 27.1, df = 2, p < 0.001). Overall, S. sahulensis were significantly more likely to exhibit shark bite scars than T. aduncus (χ 2 = 26.1, df = 1, p < 0.001) yet there was no difference in bite presence between T. truncatus and other species ( S. sahulensis: χ 2 = 0.29, df = 1, p = 0.59; T. aduncus: χ 2 = 0.29, df = 1, p = 0.59). Dolphins found in open water habitats were significantly less likely to exhibit shark bite scars than those found in sheltered habitats (open = 16.3%, n = 160; sheltered = 42.6%, n = 402 ; χ 2 = 33.7, df = 1, p < 0.001). However, the results differed when exploring the species differences within each habitat type; S. sahulensis were significantly more likely to have shark bite scars than T. aduncus in sheltered water environments ( S. sahulensis = 51.5%, T. aduncus = 35.5%: χ 2 = 9.48, df = 1, p = 0.002), but no difference was seen between species in open waters ( S. sahulensis = 35.7% , T. aduncus = 14.9% : χ 2 = 2.60, df = 1, p = 0.11) (Figure 6). 3.3.2 | Factors influencing shark bite presence The top-ranked GLM indicated three variables, species, habitat, and age had an influence on shark bite presence; however, neither average group size nor average depth were significant (model selection is listed in Table S1). Species differences showed that S. sahulensis were significantly more likely to exhibit shark bite scarring than T. aduncus (Figure 7a). The interaction between age class and habitat was also significant, demonstrating that non-calves in sheltered habitats were more likely to exhibit shark bites than non-calves in open habitats or calves in either habitat type (Figure 7b, Table 3). 3.4 | Frequency of shark bite scarring between species GLM results for number of bites showed S. sahulensis had a significantly higher mean number of bites per bitten individual (1.71 ± 0.952 bites ( n = 101)), compared to T. aduncus (1.26 ± 0.586 bites ( n = 122)) (Figure S1, Table S1). No other predictors were found to influence the number of bites per individual (Table S2). 4 | DISCUSSION The ecological importance of predator-prey relationships is key in shaping marine communities; however, predation risk is often overlooked for many dolphin populations. This study addresses this gap for SEQ, providing the first sympatric dolphin species predation risk assessment across multiple habitats in the region, and only the second study globally to examine this risk across a range of habitats (i.e., open, coastal waters and sheltered embayments). All five dolphin species examined experienced shark predation attempts, indicating shark predation is a threat across all dolphin species in the region. Through analysis of fresh bites, G. cuvier and C. carcharias were identified as the main predators responsible for bite wounds on dolphins in the region, primarily targeting the peduncle. However, as the scars identified only represent the ‘failed’ predation attempts (Heithaus, 2001b, Smith et al. , 2018), the shark predation risk provided here must be considered a minimum estimate of predation in the region. 4.1 | Distribution of shark bite scarring The majority of shark bite scarring was present on the peduncle for both S. sahulensis and T. aduncus, followed by the anterior (for S. sahulensis ) or mid-flank ( T. aduncus ) . Comparatively, the head and dorsal fin regions had the lowest amount of scarring present. This pattern is consistent with other studies, that suggest dolphins turn their dorsal side towards the shark to evade an attack and protect their vital organs located closer to their ventral side (Cockcroft, 1989, Heithaus, 2001b, Smith et al. , 2018). Consequently, bites to the ventral side or head of the dolphin are likely to be fatal (Heithaus, 2001b), explaining the absence of bites in these body regions as individuals are unlikely to survive these predation events. Additionally, sharks are known ambush predators that likely commence predation attempts from below and out of the field of visual or acoustic detection (Geraci et al. , 1978), particularly while the dolphin is surfacing to breathe (Heithaus and Dill, 2002, Smith et al. , 2018). It is important to acknowledge the lower number of bites on the head and absence of bites on the ventral region could be related to a lack of photographic coverage, and for S. sahulensis the mid-flank region often did not fully break the surface of the water. We therefore caution that some dolphin body regions are underrepresented, these records of unsuccessful predation attempts should be considered as minimum estimates of shark predation frequencies on dolphins in SEQ waters. 4.2 | Shark and dolphin habitat overlap Two large shark species, G. cuvier and C. carcharias were identified as the primary predatory species impacting dolphins in SEQ (based on photographs of open and intermediate bites). Although direct predatory observations on dolphins by these species are scarce, dietary analysis of stomach contents has revealed that ontogenetic shifts to include mammal prey occur at ~2.5m total length (TL) for C. carcharias (Clark et al. , 2023, Grainger et al. , 2020, Kim et al. , 2012). Similarly, an ontogenetic shift in prey to include marine mammals has been recorded for G. cuvier in both Hawaii (Lowe et al. , 1996) and South Africa (Dicken et al. , 2017). The latter study highlights the importance of small odontocetes, particularly T. aduncus and D. delphis , in the diets of sharks < 220 cm precaudal length (i.e., 440 cm TL see Dicken et al. (2017)). To enable mammal predation, it has been suggested that the movements of these sharks may shift to habitats where dolphin densities are higher (Bruce, 1992). Habitat use by G. cuvier and C. carcharias spatially and temporally overlap with dolphin populations at multiple life stages (Bruce et al. , 2019, Lipscombe et al. , 2020). These shark species generally occupy coastal and offshore tropical and warm temperate waters, but use of large embayments like the GSMP are also common. Both species also have wide-ranging transcontinental movements detected through satellite tracking, indicting large home ranges (Holmes et al. , 2014, Lipscombe et al. , 2020, Spaet et al. , 2020). Seasonality and prey availability are thought to drive these large-scale movements of sharks (Andrzejaczek et al. , 2025, Fitzpatrick et al. , 2012), resulting in an overlap in habitat use with inshore dolphin populations. Spatiotemporally, the number of these sharks moving through SEQ will fluctuate daily, along with other environmental drivers that determine movement behaviour (e.g., water temperature, current strength, moon phase, other prey movement, etc.). Year-round captures of both species in SEQ have been recorded for several years in the Queensland Shark Control Program (QSCP) logbooks (Department of Agriculture and Fisheries, 2025). Gear associated with the QSCP (i.e., nets and drumlines) are deployed in open coastal areas throughout SEQ, some of which also abut major river systems and the GSMP. While open water predation risk may remain relatively constant throughout the year, seasonal fluctuations in large shark presence in sheltered estuarine waters may also cause temporal increases in predation risk. For example, the return to brackish and freshwater rivers to pup in the summer months by C. leucas is part of their life history strategy (Pirog et al. , 2019), and increases the overlap potential with any inshore dolphin populations present. Stomach contents analysis confirm dolphin presence in C. leucas diets, although, dolphins only seem to represent a small proportion of their diet, with elasmobranchs and teleost’s being the most common prey (Cliff and Dudley, 1991, Tinhan and Wells, 2021). The dietary difference might be attributed to the smaller size of adult C. leucas (Tillett et al. , 2011) compared to larger G. cuvier and C. carcharias (Burgess et al. , 2014, Meyer et al. , 2014), potentially limiting their ability or need to prey on dolphins. Consequently, despite extensive spatial overlap with dolphins, only two bites in this study were attributed to C. leucas , and both occurred on S. sahulensis . This suggests although dolphins may not be preferential prey for C. leucas , S. sahulensis are experiencing greater cumulative predation risk from large sharks due to their habitat overlap with all three predating species, potentially explaining their higher bite scar prevalence observed overall. 4.3 | Habitat as a driver for shark bite prevalence Dolphins in sheltered waters exhibited higher shark bite scarring rates than those in open waters, indicating elevated predation risk in sheltered habitats. This pattern likely reflects a combination of factors that concentrate predation risk in the shallow, sheltered habitat. The dolphins and all three of the predatory shark species identified are known to utilise embayment habitats due to the abundance of prey (Heithaus, 2001a, Heithaus and Dill, 2006, Meager et al. , 2018), increasing the potential predator-prey encounters. Further, the dolphin’s acoustic detectability is reduced in the turbid, shallow waters, increasing the success rate of shark predatory attempts in such habitats (Ebert, 1991, Heithaus, 2001a, Heithaus and Dill, 2002). Sheltered waters surrounded by land are known to constrain the possible number of escape routes and decrease manoeuvrability of dolphins during predatory attempts from sharks compared to open waters where individuals have greater opportunity to evade the attack (Heithaus and Dill, 2002). Lastly, although not a significant predictor, dolphin group sizes in sheltered waters were often smaller than observed in open waters (Hume, pers. obvs.) which may contribute to the increase in predation attempts. Throughout the animal kingdom, social species with larger groups often result in increased collective vigilance and predator detection success (Beauchamp, 2003, Cresswell and Quinn, 2011, Roberts, 1996). Similarly, this has been seen with group size patterns in Shark Bay, WA, where T. aduncus formed larger groups in shallow habitats, where G. cuvier shark predation risk is known to be elevated (Heithaus and Dill, 2002). The slight reduction in group size in our sheltered habitat may therefore reduce the dolphin’s ability to successfully detect predators, contributing to the higher shark bite rates recorded. 4.4 | Interspecific differences in predation risk Our findings suggest S. sahulensis face greater predation risk than T. aduncus populations in SEQ. Although both species are coastal dolphins with relatively sympatric habitat selection (Chilvers et al. , 2005, Parra, 2006), interspecific differences in dolphin behaviour and spatio-temporal use may be driving this disparity in predation risk. S. sahulensis more often utilise shallower, estuarine habitats than T. aduncus (Jefferson and Rosenbaum, 2014), exposing them to increased C. leucas interactions. This increase in interactions could be occurring from sub-adult C. leucas still residing in the area that are learning to forage on larger prey (Heupel et al. , 2007, Smoothey et al. , 2019). The ontogenetic shift to targeting larger prey items like marine mammals typically occurs at ~2m in length, coinciding with increased jaw gape, tooth strength, and energetic requirements (Goodman et al. , 2022, Werry et al. , 2011). This size-related ontogenetic shift may explain why C. leucas bites appear on S. sahulensis . We propose that younger C. leucas learning to forage on larger prey will result in a higher number of unsuccessful predation attempts on these dolphins, resulting in more delphinids surviving (i.e., non-lethal bites) and presenting as shark bite scars. Additionally, these unsuccessful predation attempts also quickly form learned behaviours by young dolphins to develop strategies to avoid sharks, like choice of habitat selection and larger group sizes (Heithaus, 2001a, Heithaus and Dill, 2002). Predator avoidance behaviour by dolphins has been reported worldwide, including in Western Australia, where T. aduncus were found to shift their foraging activities to deeper waters in response to increases in shark numbers (Heithaus and Dill, 2006). In South Africa, it has been postulated that T. aduncus avoid turbid waters as a potential predator avoidance behaviour (Cockcroft, 1989), whilst the higher level of predation on Indian Ocean humpback dolphins ( Sousa plumbea ) was attributed to their propensity to inhabit turbid inshore waters where predator detection may be inhibited (Cockcroft, 1991). Even in the absence of direct predation however, continued vigilance by prey species has been documented in many taxa (Favreau et al. , 2010, Le Saout et al. , 2015). For example, deer populations in Hawaii that had been isolated from predators for over 60 years still spent more than 10% of their time vigilant (Le Saout et al. , 2015). Consequently, in long-lived species like dolphins, even a low risk of predation may lead to extreme antipredator behaviours, influencing overall health and fitness (Lima, 1998). Behavioural differences between S. sahulensis and T. aduncus likely also influence the predation risk on these sympatric species. Differences in foraging strategies of these two species have been reported (Hawkins et al. , 2022, Syme et al. , 2023). T. aduncus have been observed surface foraging on epipelagic prey (e.g., bluefin trevally ( Caranx melampygus ) and hound needlefish ( Tylosurus crocodilus )) (Kiszka et al. , 2014). In contrast, S. sahulensis have been recorded predominantly foraging on demersal prey in shallower, benthic habitats (Syme et al. , 2023). This difference in foraging strategies may be influencing S. sahulensis to spend more time in shallower habitats where they are more vulnerable to predation attempts due to their reduced visual ability for predator detection while focusing on catching their prey. This phenomenon aligns with similar spatial patterns observed by Nicholls et al. (2023) in nearshore habitats of north Queensland, where shark bite presence increased with proximity to coast, suggesting an increase in prey abundance in nearshore habitats. In our study, S. sahulensis demonstrated spatial preference of slightly more estuarine waters than the T. aduncus , which is likely driven by prey distribution (Parra, 2006, Syme et al. , 2023). This species-specific microhabitat selection influences S. sahulensis to reside in closer proximity to the coast, potentially exposing them to increased predation risk which is consistent with the predation-coastal pattern previously found in Queensland waters north of our study region (Nicholls et al. , 2023). While the presence of multiple bite scars per individual suggests shark predation attempts are common, the fact that S. sahulensis had both a higher mean number of bites and a higher scar presence may also be reflecting regional variation in shark prey preference. G. cuvier are generalist predators, that opportunistically consume a wide range of prey including sea turtles, seabirds, pelagic fish and marine mammals when they are available (Fitzpatrick et al. , 2012, Heithaus and Dill, 2002), while C. carcharias show preferences for larger cetaceans and pinnipeds as they mature (Clark et al. , 2023, Long and Jones, 1996). However, despite this dietary flexibility, the higher scar rate on S. sahulensis reflects similar rates to other populations in Western Australia (WA) ( S. sahulensis = 46.0%, T. aduncus = 16.9-18.0% (Smith et al. , 2018, Sprogis et al. , 2018)) and Moreton Bay, Australia ( S. sahulensis = 48.8%, T. aduncus = 29.0% (Hawkins et al. , 2022)), suggesting a fundamental species-level difference is occurring in their ecology, behaviour and susceptibility to predation attempts, rather than a site-specific species factor alone. In contrast, predation risk from larger sharks on S. sahulensis appears lower north of our study region in the Great Barrier Reef Marine Park (GBRMP), with shark bite scar rates ~20% lower than our findings (Nicholls et al. , 2023), suggesting cetacean might not be the preferential prey for shark species in these more tropical waters. The complex tropical reef structure of the GBRMP may be providing an abundance of different prey resources to our study, namely a greater diversity of prey or preferred prey (i.e., sea turtles) that require less energetic cost to the shark (Fitzpatrick et al. , 2012), potentially resulting in decreased predation attempts on dolphins in the region. These findings demonstrate while species specific traits seem to make S. sahulensis more vulnerable to shark predation, behavioural differences and alternative prey availability for sharks can influence the overall predation risk to the dolphins. 4.5 | Age class differences in shark bite scarring Age class influenced bite scar rate of dolphins, as expected; juveniles and adults (i.e., non-calves) had more bites than calves. Non-lethal shark bite scars are expected to accumulate over time as individuals have a higher likelihood of encountering more sharks through cumulative exposure (Heithaus, 2001b, Smith et al. , 2018). Consequently, a large shark predatory attempt would likely be more successful on a smaller dolphin (i.e., a calf) and therefore likely fatal, potentially skewing patterns toward a higher prevalence of non-lethal bite marks on older individuals (Heithaus, 2001b, Wilkinson et al. , 2017). However, as exact ages could not be determined for most of the dolphins in this study, future studies should aim to quantify age-related patterns in shark bite scar accumulation in the region. CONCLUSION Predator-prey relationships are dynamic and intricate, with no single factor being able to explain the relationship between two species. The results of this study offer an insight into the predation risk of the coastal dolphins in SEQ and the species, habitat, and demographic information that can influence predator-prey interactions. This study can serve as a baseline for dolphin-shark predator-prey interactions across differing coastal habitats in the region. However, ongoing efforts to disentangle how predators and prey interact is critical as predation risk influences the ecology and evolution of both predator and prey, as well as broader ecosystem dynamics. This is particularly important in one of Queensland’s most densely populated regions, where establishing baseline knowledge is key prior to investigating potential anthropogenic impacts on marine species. Long-term research should focus on additional intrinsic and extrinsic drivers of dolphin-shark interactions (e.g., shark prey availability, dolphin foraging strategies, temporal variation in shark abundance, and seasonality), facilitate understanding of the characteristics of predation risk on dolphins, and assess its influence on the behaviour, ecology, and population dynamics of both the predator and the prey across time. These findings highlight species-specific differences in predation risk among sympatric dolphin species, suggesting habitat preferences, morphological characteristics and behavioural strategies may influence an individual’s vulnerability in shark predation risk. ACKNOWLEDGEMENTS We acknowledge the Gubbi Gubbi/Kabi Kabi and Butchulla peoples, the traditional custodians of the lands and waters on which this work was conducted and pay our respects to Elders past, present and emerging. We want to thank numerous field assistants and volunteers who have contributed to data collection in the field for the Dolphin Research Project south-east Queensland. All research was conducted under permits P-MPP-100189673 and WA0046948 and under ethics approval from the University of the Sunshine Coast Animal Ethics Committee (ANS 2287). We are grateful for the funding support provided by the Holsworth Wildlife Research Endowment & Ecological Society of Australia, the Ethel Mary Read Research Grant, the Oceania Project, CID foundation, the Winifred Violet Scott Charitable Trust and UniSC HDR funds that have allowed us to carry out this work. AUTHOR CONTRIBUTIONS Conceptualisation: BH, AL; Data curation: GH, AL; Formal Analyses: GH; Funding: GH, BH, AL; Investigation: GH, AL, BH, VP, GW; Methods: GH, BH, AL; Project admin: GH, AL, BH; Resources: GH, AL, BH; Supervision: AL, BH, KT; Writing original draft: GH; Review and editing: AL, BH, KT, VP, GW. ORCID Georgina Hume: https://orcid.org/0000-0002-8690-6721 Alexis Levengood: https://orcid.org/0000-0003-2729-5366 Gemma Webster: https://orcid.org/0009-0002-6484-9188 Kathy Townsend: https://orcid.org/0000-0002-2581-2158 Victor Peddemors: https://orcid.org/0000-0002-8743-9782 Bonnie Holmes: https://orcid.org/0000-0002-8559-9950 CONFLICT OF INTEREST STATEMENT All authors listed on this manuscript declare no conflict of interest. DATA ACCESSIBILITY STATEMENT Data supporting the result of this study will be archived on DRYAD (insert link, have currently provided data as a .zip). All the required data are uploaded as supplementary material FIGURE LEGENDS FIGURE 1: Study site location in south-east Queensland, Australia, inclusive of the ‘sheltered’ waters of the Great Sandy Marine Park (orange) and the ‘open’ coastal waters of the Sunshine Coast (teal). FIGURE 2 : Outline of a dolphin ( Tursiops spp.) illustrating the body observed for the presence of shark bite scars. FIGURE 3: Shark bite wounds on Sousa sahulensis (a, c) and Tursiops aduncus (b) photographed in the Great Sandy Marine Park, Queensland. a) represents an ‘Open’ (O) wound, b) represents an ‘Intermediate’ (I) wound, c) represents a ‘Healed’ (H) scar. FIGURE 4: Percentage of individual dolphins exhibiting shark bite scarring ( Delphinus delphis, Orcaella heinsohni , Sousa sahulensis, Tursiops aduncus and Tursiops truncatus ) from the Great Sandy Marine Park (sheltered), and the Sunshine Coast (open), Queensland, Australia. The grey area represents the percentage of each species that did not exhibit shark bite scarring, and ‘ n ’ represents the number of individuals of that species in the study. FIGURE 5: Heatmap of the distribution of shark bite scars between 2022-2025 across different body regions for Sousa sahulensis (a) and Tursiops aduncus (b) in south-east Queensland. Darker shading indicates higher bite occurrence. FIGURE 6: Presence of shark bite scarring in Sousa sahulensis and Tursiops aduncus for which photographs exist of both sides of each individual within the Great Sandy Marine Park (sheltered), and the Sunshine Coast (open), Queensland, Australia. The grey area represents the percentage of each species that did not exhibit shark bite scarring, and ‘ n ’ represents the number of individuals of that species in the study. 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Keywords comparative description marine population ecology vertebrate Authors Affiliations Georgina Hume 0000-0002-8690-6721 [email protected] University of the Sunshine Coast View all articles by this author Alexis Levengood University of the Sunshine Coast Engineering and Science View all articles by this author Gemma Webster University of the Sunshine Coast Engineering and Science View all articles by this author Kathy Townsend University of the Sunshine Coast - Fraser Coast Campus View all articles by this author Victor Peddermors NSW Department of Wild Fisheries View all articles by this author Bonnie Holmes University of the Sunshine Coast Engineering and Science View all articles by this author Metrics & Citations Metrics Article Usage 376 views 188 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Georgina Hume, Alexis Levengood, Gemma Webster, et al. 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