Marine Biology (2021) 168:80 https://doi.org/10.1007/s00227-021-03886-z ORIGINAL PAPER Intra‑specific variation in movement and habitat connectivity of a mobile predator revealed by acoustic telemetry and network analyses Mario Espinoza1,2 · Elodie J. I. Lédée1 · Amy F. Smoothey3 · Michelle R. Heupel4,5 · Victor M. Peddemors2 · Andrew J. Tobin1 · Colin A. Simpfendorfer1 Received: 15 January 2021 / Accepted: 18 April 2021 / Published online: 3 May 2021 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract Few studies have considered linkages of mobile predators across large spatial scales despite their significant and often critical role in maintaining ecosystem function and health. The bull shark (Carcharhinus leucas) is a large, widespread coastal predator capable of undertaking long-range movement, but there is still limited understanding of intra-regional differences in movement and habitat connectivity across latitudes within the same coastline. This study used acoustic telemetry data and network analyses to investigate long-range movements, residency patterns and seasonal habitat linkages of sub-adult and adult C. leucas along the east coast of Australia. Our results revealed that C. leucas tagged in Sydney Harbour were mainly present within this temperate estuary in summer and autumn; the rest of the year individuals were detected in tropical and subtropical habitats from southern and central Queensland. In contrast, the detection probability of C. leucas tagged in the Townsville Reefs (central Great Barrier Reef) peaked in spring, with a portion of the tagged population migrating south during the summer months. Differences in residency time between tagging locations were also detected, as all C. leucas tagged in Sydney Harbour were absent between June and November, but 35% of the tropical-reef tagged population remained resident year-round. Network analyses complemented these findings by revealing different seasonal habitat use between regions, thus highlighting complex seasonal-habitat linkages of C. leucas along the coast. Our findings support the hypothesis that the timing, duration, and drivers involved in the long-range movements and connectivity of sub-adult and adult C. leucas vary between latitudinal regions, most likely driven by the interaction between seasonal temperature changes, foraging and reproduction. Introduction Responsible Editor: J.K. Carlson. Reviewers: undisclosed experts. * Mario Espinoza [email protected] 1 Centre for Sustainable Tropical Fisheries and Aquaculture and College of Marine and Environmental Sciences, James Cook University, Townsville, QLD 4811, Australia 2 Centro de Investigación en Ciencias del Mar y Limnología, Universidad de Costa Rica, San José 11501‑2060, Costa Rica 3 NSW Department of Primary Industries, Sydney Institute of Marine Science, Mosman, NSW 2088, Australia 4 Australian Institute of Marine Science, PMB No 3, Townsville, QLD 4810, Australia 5 Integrated Marine Observing System (IMOS), University of Tasmania, Private Bag 110, Hobart, TAS 7001, Australia Long-range movement and ecological linkages across large spatial scales are common in a wide range of taxa (Sims et al. 2009; Bauer and Hoye 2014; Lea et al. 2015), yet drivers of animal movement are often unclear. For many animals, reproduction is the major force behind long-range movement (Rustadbakken et al. 2004; Norris et al. 2004; Crossin et al. 2009). Given that moving long distances is a highly energetic process for animals, population-level decisions leading to long-range reproductive movement must prove advantageous. In some species, for example, individuals often return to their exact birth place or region (natal philopatry), often travelling long distances to breeding or birthing habitats that provide protection for young (e.g. nursery grounds) or access to other mature adults (Heupel et al. 2007; Brothers and Lohmann 2015; Chapman et al. 2015). Animals also move in response to seasonal environmental 13 Vol.:(0123456789) 80 Page 2 of 15 changes (Ritz et al. 2011; Lea et al. 2015), predation risk (Skov et al. 2011), density-dependent processes (Grayson and Wilbur 2009; Mysterud et al. 2011), and even in response to habitat modification and/or fragmentation (Norris et al. 2004; Rittenhouse and Semlitsch 2006). Therefore, understanding how animals respond to biological and environmental drivers is important to determining the timing and duration of movements and ecological linkages. Knowledge of an animal’s spatial ecology and movement dynamics is also crucial to many aspects of its management and conservation such as identifying critical habitats (Heupel et al. 2007; Papastamatiou et al. 2015a, b), improving reserve performance (Olds et al. 2012; Espinoza et al. 2015a, b), evaluating habitat connectivity (Jordán et al. 2003; McMahon et al. 2012), assessing population dynamics and persistence (Vuilleumier et al. 2007; Cushman et al. 2013) and predicting changes to species’ distributions under future climate conditions (Niella et al. 2020). Ultimately, information on how long animals spend in specific habitats can help define their role in an ecosystem (Heithaus et al. 2014). Some studies also suggested that wide-ranging marine predators such as sharks have the ability to transport nutrients, energy, and even other organisms throughout their journeys, not only acting as energy links across large spatial scales, but also affecting local diversity and food web dynamics (McCauley et al. 2012a, b; Bauer and Hoye 2014; Williams et al. 2018). Therefore, quantifying long-range movements and habitat linkages of wide-ranging sharks over large spatial scales could shed light on how ecosystems are inter-connected and the role of “mobile link species” (i.e. species that play disproportionately important roles in the stability and function across ecosystems; Lundberg and Moberg 2003). The bull shark (Carcharhinus leucas) is a large, coastal predator found in a wide variety of tropical, subtropical and riverine habitats worldwide (Thorson 1971; Werry et al. 2012; Simpfendorfer et al. 2005; Espinoza et al. 2016; Smoothey et al. 2016). This species is capable of undertaking long-range movements along the coast (Daly et al. 2014; Espinoza et al. 2016), but there is still limited understanding of intra-regional differences in movement and habitat connectivity across latitudes. Previous findings of acoustically tagged adult C. leucas showed that some individuals moved from tropical reef habitats in the central Great Barrier Reef (GBR) of Australia to temperate estuarine and riverine habitats in New South Wales (Heupel et al. 2015; Espinoza et al. 2016), thus making it an ideal mobile link species with which to examine broad-scale patterns of habitat connectivity across ecosystems. Interestingly, Espinoza et al. (2016) revealed that only a portion of the GBR tagged population (mainly females) moved long distances, while the rest spent a significant amount of time on coral reefs near their tagging array in the central GBR. Conversely, catch and movement data from Sydney Harbour (SYH) in New 13 Marine Biology (2021) 168:80 South Wales (Australia), indicated that all C. leucas leave this temperate estuary during winter (Smoothey et al. 2016, 2019; Lee et al. 2019). These findings suggest that adult C. leucas have distinct residency and connectivity patterns across their latitudinal distribution. Given the growing body of evidence that large coastal sharks often move between temperate and tropical regions (Lea et al. 2015; Ferreira et al. 2015; Espinoza et al. 2016), we combined existing telemetry data with network analysis to investigate long-range movements, residency patterns and seasonal habitat linkages of C. leucas along the east coast of Australia. Network analysis was applied to examine the relationship between nodes (acoustic receiver arrays), where a network represents connections (or edges, representing shark movements) between nodes used to explore migratory movements. Habitat attributes were linked to node properties to examine their relative importance in the network, and consequently in movement and connectivity. Specifically, we examined: (i) long-term patterns of shark residency; (ii) the effects of biological and environmental drivers on shark residency; (iii) differences in seasonal movement between C. leucas tagged in a tropical and temperate system; and (iv) the linkages and habitat connectivity of C. leucas along the East coast of Australia. Materials and methods Acoustic monitoring Fourteen acoustic receiver arrays (VR2W, Vemco Ltd. Nova Scotia) were used to examine broad-scale movement and connectivity of C. leucas along the east coast of Australia (Fig. 1a). Nine of these arrays were located in tropical and subtropical waters of Queensland (QLD), including: Low Isles—LOI; Orpheus Island—ORI; Townsville Reefs—TSV; Cleveland Bay—CB; Capricorn Bunker reefs including Heron, Sykes, One Tree Island—HI; Lady Elliot Island—LEI; Fraser Island—FI; Sunshine Coast—SC; and Moreton Bay—MB. The other five arrays were in subtropical and temperate waters of New South Wales (NSW), including: Clarence River—CR, Port Macquarie—PMA; Newcastle—NEW; Sydney Harbour—SYH; and Wollongong—WOL. Along the latitudinal gradient (tropical, subtropical and temperate), each receiver array covered a wide range of zones (coastal, inshore, riverine/estuarine, embayment and reef) and habitat types (rocky and coral reef, sandy interspaced with reef, sand/mud/mangrove, sandy bottom and atoll) (see supplementary methods S1A for more details). The number of receivers varied by site: LOI (n = 15), ORI (n = 33), TSV (n = 56), CB (n = 74), HI (n = 50), LEI (n = 6), FI (n = 14), SC (n = 9), MB (n = 29), CR (n = 12), PMA (n = 6), NEW (n = 5), SYH (n = 46) and Marine Biology (2021) 168:80 Page 3 of 15 80 Fig. 1 Location of acoustic receiver arrays (colour dots) used to monitored the movement of bull sharks (Carcharhinus leucas) in Queensland (QLD) and New South Wales (NSW), east coast of Australia (a). Panels b–i show the number of male and female sharks moving from/ to an array during each season. Colours represent the different arrays and the width of the colour bands within the circle plots indicate the number of individual sharks moving from/to each array. The scale of each plot shows the number of sharks that moved between arrays during each season. Seasons were defined as summer (December–February), autumn (March–May), winter (June–August) and spring (September–November) WOL (n = 5). This represented a combined acoustic network of 360 receivers. Receiver arrays were deployed at various times with the earliest (CB) established in 2008, but all were deployed for the entire study period (2011–2014). Receiver arrays on HI, PMA, NEW, WOL and part of MB are supported and maintained by the Integrated Marine Observing System—IMOS (IMOS 2015). Data from these receivers was obtained via the IMOS national database. For a detailed description of receiver deployment methodology see (Knip et al. 2012; Hazel et al. 2013; Espinoza et al. 2015a, b; Zeh et al. 2015). Acoustic detection range varied among receiver arrays, but typically ranged from 200 to 400 m. Sharks were captured in TSV and SYH using a variety of standard fishing methods, including long-lines, drop-lines and rod-reel (see Heupel and Simpfendorfer 2014; Espinoza et al. 2015a, b; Heupel et al. 2015; Smoothey et al. 2016 for a description of sampling methodology). All captured individuals were measured to the nearest cm (fork length—FL; total stretch length—TL), sexed and surgically implanted with V16 acoustic transmitter (Vemco Ltd. Nova Scotia) 13 80 Page 4 of 15 using methods described by Heupel and Hueter (2001). Each transmitter emitted a unique identification code and was programmed on a pseudo-random repeat rate of 40–100 s (TSV) or 30–90 s (SYH) with estimated battery life of 824 and 3260 days, respectively. Based on published size-maturity state data, all C. leucas tagged in this study were considered sub-adults or adults (Cruz-Martínez et al. 2005). Seasonal patterns of shark presence A set of generalized additive mixed models (GAMM) was used to examine seasonal and inter-annual changes in shark detection probability at TSV and SYH. These two arrays were chosen as the focal sites of the study based on their large acoustic coverage and tagging effort targeting subadult and adult C. leucas. Moreover, these arrays allowed comparison of long-term residency and movement behaviours. Seasonal changes in detection probability were only restricted to the monitoring period from 2011 to 2014. Models included sex, fork length (cm), bottom water temperature (°C), monitoring year and day of year as predictors. Mean daily water temperature data for TSV (recorded from the reef slope at 10–15 m depth) and SYH (recorded inside the estuary at 5–10 m depth) arrays were obtained from the Australian Institute of Marine Science weather stations (http:// data.aims.gov.au) and the Australian Bureau of Meteorology (http://bom.gov.au), respectively. Daily shark presence/ absence at each receiver array was the response variable; therefore, models were fitted with a binomial distribution. An individual was considered present at any given array if two or more detections were recorded on any single day. The variable day of year (spline smoother) provided intra-year variation to identify seasonal changes in shark presence at the two main tagging locations (TSV and SYH), whereas year (factor) allowed identification of inter-annual patterns. To account for unequal sample size of sharks tagged across years and the repeated-measures nature of the data, each individual was treated as a random effect and autocorrelation structure (corCAR1(form = ~ s(day of year) | year) was included when appropriate (Zuur et al. 2014). In the Townsville Reefs, sharks were monitored from 2012 to 2014, whereas in Sydney Harbour monitoring time ranged from 2011 to 2014. Model performance and selection were assessed using the Akaike Information Criterion (AIC). The output from the best fitted model (model with the lowest AIC value) was then examined to assess the effect of each predictor. Models were tested for multicollinearity using the variance inflation function “VIF” in the AED package (Zuur et al. 2009) and by examining pairwise correlation plots between predictors. Predictors with VIF values > 5 were dropped from the model. GAMMs were implemented using the “gamm” function from the “mgcv” library in R v.3.0.2 (Zuur et al. 2014; R Development Core Team 2019). 13 Marine Biology (2021) 168:80 Movement and habitat connectivity A matrix representing the movement of individuals from/ to each receiver array was constructed to quantify the following movement events: (i) individuals not detected—the proportion of monitored individuals that were not detected by any receiver array during a particular season; (ii) detected at other arrays—the proportion of monitored individuals that were detected at receiver arrays other than their tagging array during a particular season; (iii) stayed at tagging array—the proportion of monitored individuals that were detected within their tagging array during a particular season; and (iv) returned to tagging array—the proportion of monitored individuals that were detected at other arrays but returned to their tagging array within the same season. In this matrix, the total number of individuals tagged at each array (TSV and SYH) for the entire monitoring period was combined at the array level. Seasonal movement events were also investigated. Seasons were defined as summer (December–February), autumn (March–May), winter (June–August) and spring (September–November). A goodness-of-fit test (χ2) was used to determine if the proportion of monitored individuals recorded for each movement event and during each season differed from expected. The movement matrix was also used to quantify the degree of shark connectivity between receiver arrays. A modified circular plot (“connectivity plot”) was used to visualise the number of movements of male and female individuals from/to each array and during each season (see Espinoza et al. 2016). Connectivity plots were implemented using the “circos.trackPlotRegion” function from the “circlize” package (Gu et al. 2014) in R v.3.0.2 (R Development Core Team 2019). Network analysis Detection data were first combined at the array level, and then aggregated per season to create an inter-array movement matrix for each individual-season combination. This movement matrix counted the number of individuals present at, and relative movement of individuals between, receiver arrays during each season. We used a data filtering procedure at the array level to remove potential “false detections” based on previous work by Lédée et al. (2015), where only detections at the same array that were ≥ 5 min apart were included in the network. Relative movements were defined as the number of times individuals moved between two arrays divided by the total number of movements within its space use (i.e. total number of edges in the network—Jacoby et al. 2012). This matrix was used to create weighted and directed seasonal networks for each individual that reflected the extent of space use during the entire monitoring period. To determine whether shark movements exhibited nonrandom patterns, a link re-arrangement (i.e. permutation) Page 5 of 15 80 Marine Biology (2021) 168:80 was performed on each network using a bootstrap approach (10,000 iterations) (Croft et al. 2011). See supplementary methods S1B for more details. Network metrics of individual sharks such as the number of nodes, edges and diameter were calculated using “igraph” in R statistical package v.3.0.2. Network diameter measured the longest path between any pair of arrays in the network and was an indicator of the size of the network (Csardi and Nepusz 2006). To account for long-range dispersal between receiver arrays, network diameter was standardised by the Euclidean distance between the centroid of the arrays (i.e. central position of all of the receivers in the array). A generalized linear model (GLM) was used to examine the influence of the tagging array (TSV and SYH), sex and season on network metrics (e.g. number of nodes, number of edges and network diameter) of all sharks combined. Each individual represented a unique network, and thus an independent observation. Significant differences of factors and interactions of the best fitted model were evaluated with maximum likelihood ratio tests (χ2, p < 0.05). Models were tested for multicollinearity using the “VIF” function in the AED package (Zuur et al. 2009) and by examining pairwise correlation plots between predictors; predictors with VIF values > 5 were dropped from the model. GLMs were implemented using the “glm” function in R v.3.0.2 (R Development Core Team 2019). Two‑mode networks All detection data (presence/absence) for individuals tagged at the Townsville Reefs and Sydney Harbour were grouped by sex and used to create matrices of the frequency of habitat type use during each season. Given that the matrices were based on two “modes” (habitat and season; supplementary methods S1A), the network created was bipartite, with one set of nodes representing habitats and the other representing seasons producing two-mode networks (Opsahl 2013). The edges between nodes existed only between the two Table 1 Summary information of bull sharks (Carcharhinus leucas) monitored along the East coast of Australia Tagging array Townsville Reefs Sex Male Female Sydney Harbour Sex Male Female N different sets, and, therefore, were not directed. Two-mode network analyses allowed examination of seasonal habitat use and connectivity of male and female C. leucas. Matrix rows represented habitat types, columns represented seasons and cell counts indicated the presence of an individual in a particular habitat type and during a particular season (see supplementary methods S1C for more details). A Quadratic Assignment Procedure (QAP) correlation was used to test for seasonal use similarities between sexes within each tagging array and between tagging arrays for each sex using the “sna” package (Butts 2020). Finally, canonical correspondence analysis (CCA) was used to investigate seasonal patterns of coastal and coral reef use by C. leucas. CCA was calculated for each tagging array and sex in R using the “vegan” package (Oksanen 2020). Results Data from 73 subadult and adult C. leucas tagged between 2009 and 2013 were examined: 33 from the Townsville Reefs (8 males, 25 females) ranging in size from 150 to 259 cm FL, and 40 from Sydney Harbour (28 males and 12 females) ranging in size from 207 to 314 cm FL (Table 1). Overall, C. leucas were monitored in TSV for 468–825 days, and in SYH for 853–2281 days (Table 1). The number of days individuals were detected in TSV did not differ between sexes (TSV: Kruskal–Wallis χ2 = 0.0004, df = 1, p = 0.983; CR: Kruskal–Wallis χ2 = 3.08, df = 1, p = 0.079). However, on average males tagged in SYH were detected on more days than females (Kruskal–Wallis χ2 = 5.58, df = 1, p = 0.018; Table 1). Seasonal patterns of shark presence Based on the GAMM model selection, sex was excluded from further analyses (see supplementary Table S1). The final model included fork length, temperature, day of year Fork length (cm) Days monitored Days detected Range Mean ± SD Range Mean Range Mean ± SD 33 150–269 201.8 ± 25.2 468–825 712 ± 118 1–474 93 ± 108 8 25 40 176–215 150–269 207–314 197.2 ± 14.9 203.2 ± 27.8 259.8 ± 25.0 617–825 468–825 853–2281 746 ± 83 701 ± 127 1515 ± 385 6–474 1–277 3–215 137 ± 183 79 ± 69 76 ± 61 28 12 212–298 207–314 258.2 ± 21.9 263.4 ± 32.1 866–2281 853–1603 1589 ± 405 1344 ± 280 10–215 3–103 91 ± 65 43 ± 35 N—Number of sharks tagged; days monitored—Number of days from the tagging date to the end of the study period 13 80 Page 6 of 15 Marine Biology (2021) 168:80 and year (Table 2). Fork length had no effect on shark presence, however, a significant effect of day of year, temperature and year were found at both tagging locations, indicating that shark detection probability varied in response to season and years (Table 2; Fig. 2). Models showed an increase in detection probability with increasing water temperature (Fig. S1, S2), but this relationship was stronger in sharks monitored in temperate waters as all individuals left SYH during late autumn/early winter when water temperature dropped. Water temperature in SYH fluctuated from 10.0 to 19.9 °C (14.3 ± 1.7 °C) in the winter and from 14.4 Table 2 Selected generalized additive mixed model (GAMM) showing seasonal and inter-annual effects of bull shark detection probability in Townville Reefs—TSV (R2 = 0.045) and Sydney Harbour— SYH (R2 = 0.29) Model and terms Townsville Reefs (N = 33) Fork length Temperature Year S (day of year) Sydney Harbour (N = 40) Fork length Temperature Year S (day of year) df F-statistic p 1 1 1 7.9 0.5 23.9 25.8 115.7 0.486 < 0.001 < 0.001 < 0.001 1 1 1 8.2 1.6 86.2 281.0 509.0 0.198 < 0.001 < 0.001 < 0.001 The full model evaluated had the following structure: p (detection) ~ sex + FL + temperature + year + s (day of year) + (1 | tag). The response variable was expressed as probability that a shark was present within the array. The day of year was included as a spline smoother. N—number of individuals tagged in each receiver array. p values in bold are significant Fig. 2 Detection probability of bull sharks (Carcharhinus leucas) within their tagging array based on the day of the year. Only individuals tagged at the Townsville Reefs (TSV) and in Sydney Harbour (SYH) were included the analysis across years. As a reference, January–February correspond to 0–50 days, whereas September– October to 250–300 days 13 to 31.7 °C (21.8 ± 2.1 °C) in the summer. In TSV, differences in water temperature between winter (23.6 ± 0.7 °C) and summer (28.2 ± 0.6 °C) seasons were smaller than for SYH. Twenty-seven percent of the sharks tagged in TSV were detected between 10 and 16 consecutive months, whereas only 18% of the sharks tagged in SYH were detected for five consecutive months. Individuals showed higher detection probability in TSV array between September and October, and a higher detection probability in the SYH array between January and February (Fig. 2). Models from both arrays also revealed a significant decrease in shark detection probability between monitoring years (Table 2), suggesting that some individuals left their array and did not return the following year. Movement and habitat connectivity A large proportion of C. leucas monitored in this study (80%) moved between receiver arrays, often exhibiting high degrees of connectivity along the entire East coast of Australia (Fig. 1). However, there were substantial differences between the two tagging locations, with 98% of the sharks tagged in SYH detected in two or more arrays compared to 58% of TSV individuals. The number of arrays used by sharks also varied between tagging locations (Kruskal–Wallis χ2 = 29.82, df = 1, p < 0.001). For example, SYH individuals were detected in more than twice the number of arrays (5.1 ± 1.9 arrays) than TSV individuals (2.3 ± 1.4 arrays). In fact, six sharks from temperate estuarine waters in SYH were detected in eight or more receiver arrays, travelling minimum linear distances of 1822.5 ± 48 km. Moreover, female C. leucas tagged in SYH used a larger number of arrays (6.2 ± 1.7 arrays) than males (4.6 ± 1.8 arrays) Page 7 of 15 80 Marine Biology (2021) 168:80 (Kruskal–Wallis χ 2 = 5.88, df = 1, p = 0.015). In TSV, although females were detected in more arrays (2.4 ± 1.5 arrays) than males (1.8 ± 0.9 arrays) and undertook longer excursions, no significant differences in the number of arrays used between sexes were detected (Kruskal–Wallis χ2 = 0.51, df = 1, p = 0.473). None of the individuals tagged in SYH (males and females) stayed within this array; however, all eventually returned to their tagging array after leaving. In contrast, 63% of male and 40% of female C. leucas tagged in TSV remained at or were only detected within this array (Fig. 3). For example, during summer, 82% of the tagged population from SYH either remained in (40%) or made return trips (42%) (χ2 = 144.7, df = 9, p < 0.001; Fig. 3) to the array. In contrast, all C. leucas tagged in SYH were absent from this array during winter. During this non-resident period, 23% of the SYH tagged sharks were detected at arrays within QLD waters, but 77% were not detected at any other array. Only 5% of individuals returned to SYH during the spring, with most return events observed during summer (42%) and autumn (45%) (Fig. 3). In contrast, movement events did not differ between seasons for sharks tagged in the TSV (χ2, p > 0.05). While a larger proportion of C. leucas tagged in TSV were recorded during winter (76%) and spring (89%), differences were not significant. Seasonal network analysis From all the networks constructed (N = 89), only one network was random (χ2, p > 0.05). This network was excluded from subsequent analysis. Results from GLMs showed that network metrics were mainly influenced by tagging location (Table 3; Fig. S3). Networks from individuals tagged in SYH had greater numbers of nodes and edges than networks from TSV. In addition, individuals tagged in SYH had a significantly larger network diameter than TSV (Table 3; Fig. S3). Models showed that network metrics did not differ between sexes; however, movements between receiver arrays were more common during summer, thus revealing a seasonal effect on the number of edges. Habitat associations Two-mode network visualization showed that tropical outer reefs were the most important habitats (larger node size) for male (Fig. 4a) and female (Fig. 4b) C. leucas tagged in the TSV, particularly during winter and spring, respectively. In summer, temperate inshore sandy habitats interspersed with reef were most important for sharks tagged in SYH (Fig. 4c, d). Overall, sharks tagged in SYH used more and various habitat types all along the coast compared to shark tagged in TSV which mainly used tropical and sub-tropical habitat types. The QAP correlation showed that male and female C. leucas tagged in SYH and the TSV had similar networks (i.e. similar seasonal use of the arrays). Females from SYH showed similar seasonal use of each array (Table S1). Although some differences in seasonal habitat use were observed in females tagged in TSV and Clarence River (30% similarity in two-mode network), these were not significant (Table S1). Males tagged in TSV and Clarence River had significant differences in their seasonal habitat use (Table S1). For sharks tagged at TSV, latitudinal movements along the coast and inshore-offshore movements (Fig. 5a, b) explained between 77% (female) and 100% (male) of their seasonal habitat use (Table S2); with an increase in individual variations (i.e. bigger circles) in summer and autumn compared to other seasons (Fig. 5a, b). Movement between inshoreoffshore arrays and the use of a wide range of coastal habitats available were more important for individuals tagged in SYH (Fig. 5c, d), explaining between 52% (female) and 64% (male—Table S2). There were larger individual variations in habitat use in spring and to some extent winter (male) compared to other seasons (Fig. 5c, d). Furthermore, canonical correspondence analyses identified a tropical coastal embayment with sandy habitat (Cleveland Bay—See supplementary methods S1A) as a single important habitat type for females tagged in TSV and both females and males tagged in SYH; most specifically in spring (Fig. 5b, c, d—Table S2). Discussion This study demonstrated that subadult and adult C. leucas acoustically monitored in tropical and temperate habitats of the east coast of Australia exhibited distinct residency and connectivity patterns, thus supporting our initial hypothesis that that the timing, duration and drivers involved in the movement and connectivity of adult C. leucas vary between latitudinal regions. Acoustic telemetry data revealed that adult C. leucas were mainly present in a temperate estuary in summer and autumn, which corroborates catch and movement data previously reported by Smoothey et al. (2016, 2019). This analysis indicates that for the rest of the year, most Sydney-tagged individuals were detected at several acoustic arrays in southern and central Queensland. In contrast, detection probability of adult C. leucas tagged at tropical reefs peaked in spring, and only a portion of the female population undertook summer migrations, some of them to Clarence River in New South Wales (Espinoza et al. 2016). Differences in their residency were also detected, as all C. leucas from temperate waters were absent between June and November, but over 35% of the individuals tagged in TSV remained resident on tropical reefs year-round during our study. Network analyses supported these findings by revealing 13 80 Page 8 of 15 13 Marine Biology (2021) 168:80 Marine Biology (2021) 168:80 ◂Fig. 3 Movement events recorded for bull sharks (Carcharhinus leu- cas) tagged in the Townsville Reefs—TSV (a–d) and Sydney Harbour—SYH (e–h) during each season. Movement events were classified as: (i) individuals not detected—the proportion of monitored individuals that were not detected by any receiver array during a particular season; (ii) detected at other arrays—the proportion of monitored individuals that were detected at receiver arrays other than their tagging array during a particular season; (iii) stayed at tagging array—the proportion of monitored individuals that were detected within their tagging array during a particular season; and (iv) returned to tagging array—the proportion of monitored individuals that were detected at other arrays but returned to their tagging array within the same season different seasonal habitat use preferences between tagging locations. For instance, TSV tagged sharks had greatest affinity for offshore reefs, primarily during winter and spring, whilst during the summer and autumn they were spread between inshore reef and coastal habitats (QLD and NSW). Sydney Harbour tagged sharks, on the other hand, were spread over all habitats during the winter and spring, but showed high affinity to NSW coastal habitats during the summer. These results highlight complex seasonal-habitat linkages of C. leucas along the east coast of Australia. Our findings suggest that intra-regional variation in movement and residency patterns were likely due to the relatively low temperature fluctuations that C. leucas experienced in TSV (22.0–29.6 °C; 25.9 ± 1.9 °C) relative to large temperature fluctuations documented in SYH (9.9–31.7 °C; 18.3 ± 3.6 °C). Overall, tropical tagged sharks exhibited less long-range movements and were detected for longer periods (27% of C. leucas tagged in TSV spent more than ten consecutive months in the central GBR), whereas temperate tagged sharks showed relatively high movement variation, were only present inside SYH during summer and autumn (warmest seasons), and all departed before winter. Similar patterns of shark catch rates and residency patterns within SYH were reported for subadult and adult C. leucas by Smoothey et al. (2016, 2019), further suggesting that this species was more abundant in this estuary when surface water temperature was between 19 and 23 °C. In temperate estuaries, many elasmobranchs are seasonally abundant as these habitats generally experience large temperature fluctuations (Carlisle and Starr 2009; Bansemer and Bennett 2011; Espinoza et al. 2011). Consequently, temperate coastal species tend to use shallow bays and estuaries during warmer months not only for feeding and reproduction, but also because these habitats may offer thermal physiological advantages (e.g. increased growth, reproduction and gastric evacuation rates) relative to colder coastal areas (Hight and Lowe 2007; Espinoza et al. 2011; Jirik and Lowe 2012). Alternatively, it is also possible that C. leucas may exhibit geographic variations in temperature preferences along the Page 9 of 15 80 east coast of Australia, which is consistent with findings from Lear et al. (2019). Large coastal sharks tend to roam more widely during summer, often making repeated seasonal movements to specific breeding/mating grounds (Bansemer and Bennett 2011; Chapman et al. 2015), or to exploit seasonally abundant resources (Sims et al. 2003; Barnett et al. 2011; Lea et al. 2015). While most sharks tracked in our study moved longer distances during summer than in other seasons, networks from individuals tagged in NSW were typically larger and more complex than sharks tagged in tropical waters, mainly because more individuals undertook longer migrations to the central and southern GBR during winter and spring, before moving back to SYH in the summer (> 3200 km round-trip). Similar findings were reported by Lea et al. (2015), who showed that tiger sharks (Galeocerdo cuvier) made long-range oceanic movements during summer potentially for foraging, but showed repeated site fidelity to overwinter at insular reef habitats in the Caribbean. In contrast, only approximately half of the tropical population of C. leucas left their tagging array in summer, and only one individual was detected in New South Wales, suggesting not all C. leucas undertake seasonal long-range movements and that a portion of the population restricts their movements to Queensland waters. Based on our findings, there is likely a population organization where the subadults and adults remain at the reef, especially over winter/spring and then return to summer coastal areas that are associated with their pupping grounds (i.e. natal philopatry). Adult females that stay for longer periods at the reef may be those that are not breeding that year, which is consistent with a previous study on C. leucas in the Western Indian Ocean that suggest this species has a 1 year resting period and a 4–5 month sperm storage period between mating and fertilization (Pirog et al. 2019a). Although, it is still unclear why some males also return to these locations. Interestingly, most C. leucas tagged in SYH returned from warmer tropical waters. However, a lack of evidence of reproductive behaviour (e.g. mating bites, distended cloaca, vascularised claspers, abdominal signs of pregnancy) suggests that their movement to this higher latitude region is unlikely driven by reproductive philopatry, as suggested for lower latitudes (Tillett et al. 2012). While temperature can influence the movement and physiology of tropical sharks (Speed et al. 2012; Papastamatiouet al. 2015a, b), its role as a potential trigger for movement may be more subtle than in temperate regions (Hopkins and Cech 2003; Carlisle and Starr 2009; Espinoza et al. 2011). The fact that a relatively large number of individuals tagged at TSV were present year-round suggests that factors other than temperature drive movement within tropical waters, which is consistent with findings for other reef-associated species (Chin et al. 2013; Papastamatiou et al. 2013; Heupel 13 80 Page 10 of 15 Table 3 General linear model results of factors that influenced network metrics of bull sharks (Carcharhinus leucas) monitored along the East coast of Australia Marine Biology (2021) 168:80 Effect Null Array Season Sex Array × Season Season × Sex Number of nodes Number of edges Network diameter df Dev Res. Dev. p Dev. Res. Dev. p Dev. Res. Dev. 1 3 1 2 3 0.060 0.018 0.015 0.023 0.002 1.102 1.043 1.025 1.010 0.986 0.984 0.030 0.708 0.272 0.395 0.985 0.140 0.246 0.015 0.083 0.015 2.490 2.350 2.104 2.089 2.006 1.991 0.019 0.022 0.447 0.196 0.896 19,166 1941.6 17,224 614.75 16,609 394.28 16,215 306.14 15,909 358.65 15,550 p 0.002 0.379 0.160 0.464 0.615 Network metrics included the number of nodes, number of edges and network diameter (km). p values in bold are significant. Null refers to the intercept-only model. Dev. refers to deviance and Res. Dev. to residual deviance. Significant differences were evaluated with maximum likelihood ratio tests (χ2, p < 0.05) Fig. 4 Two-mode networks of male and female bull sharks (Carcharhinus leucas) tagged in the Townsville Reefs and Sydney Harbour. Nodes are represented by the eigenvector of each habitat type (grey square) and season (coloured bubble). Arrows between nodes are the edges or movement paths, with the direction and thickness indicating the strength of the path (relative importance) linking habitat types with seasons. Seasons: summer in green, autumn in black, winter in blue and spring in red and Simpfendorfer 2014; Lea et al. 2015). Espinoza et al. (2016) hypothesized that the central GBR is an important foraging ground for C. leucas during spring, when Spanish mackerel form large spawning aggregations (Tobin et al. 13 2013). Fish aggregations such as this one, could explain the strong peak in shark detection probability observed between September and October, but also why a large proportion of individuals (85%) would return to this region. Rainfall can Marine Biology (2021) 168:80 Page 11 of 15 80 Fig. 5 Results from canonical correspondence analysis used to investigate seasonal patterns of habitat use by bull sharks (Carcharhinus leucas). Habitat types are represented by numbered squares, individual seasons by coloured triangles and seasons are represented by coloured convex hulls polygons. Seasons: summer in green, autumn in black, winter in blue and spring in red. Habitat types: (1) Tropical— Coastal embayment—Sandy, (2) Tropical—Inner Reef—Coral reef/ atoll, (3) Tropical—Outer Reef—Coral reef/atoll, (4) Subtropical— Coastal embayment—Sandy, (5) Subtropical—Coastal ocean—Rocky reef, (6) Subtropical—Riverine/estuarine—Sand/mud/mangrove, (7) Temperate—Coastal ocean—Rocky reef and (8) Temperate— Inshore—Sandy interspersed with some reef also increase coastal productivity in nearshore habitats, and thus may enhance foraging opportunities of adult C. leucas during wet periods (summer months) (Werry 2010; Knip et al. 2011), which is generally when Townsville Reefs individuals were detected at more coastal arrays. Our study suggests that long-range movements of tropical tagged sharks to subtropical estuarine habitats may be driven by reproduction. Werry (2010) reported higher catch rates of pregnant C. leucas along the southern QLD coast in summer, thus supporting our observations that mature females may be roaming more widely during wet periods as more productive nearshore habitats could increase growth rates of neonates shortly after parturition in these subtropical coastal habitats. Inter-annual breeding and philopatric behaviour can also 13 80 Page 12 of 15 explain female-biased dispersal and/or migratory patterns of large coastal sharks (Pardini et al. 2001; Papastamatiou et al. 2013; Chapman et al. 2015). In northern Australia, for example, female C. leucas are known to return to their natal estuaries to give birth (Tillett et al. 2012). However, further genetic studies along the east coast of Australia are needed to determine if C. leucas exhibits some type of reproductive philopatric behaviour, and if individuals from tropical and temperate waters form a single population (Pirog et al. 2019b). Moreover, sex ratios from the reef-based population were biased towards females, which could have limited our ability to detect male movement. Additional tagging efforts of C. leucas within tropical waters could increase our understanding of male dispersal strategies and partial migration. Even though movements differed between tagging locations, network analyses revealed that seasonal habitat use patterns of C. leucas were similar between sexes, particularly in NSW. This finding contrasted with previous studies using network analysis that showed distinct habitat preferences between male and female broadnose sevengill sharks (Notorynchuss cepedianus) in an estuary in Tasmania (Stehfest et al. 2015). Espinoza et al. (2015a, b) also revealed sex differences in the networks of grey reef sharks (C. amblyrhynchos) monitored in the central GBR, where males dispersed more than females, and thus may have different patterns of habitat use. In wide ranging coastal predators such as C. leucas, habitat use patterns may vary depending on the spatial scale. Seasonal temperature fluctuations and biological requirements are likely driving patterns of habitat use at a large spatial scale for both males and females, whereas sex and size may be more important at smaller scales (e.g. within a bay or an estuary) (Simpfendorfer et al. 2005; Curtis 2008; Werry 2010). The use of network analyses provided a powerful framework to elucidate habitat use and movement connectivity of a large wide-ranging predator at broad spatial scales (> 2000 km), thus revealing the complexities of seasonal linkages across wide latitudinal ranges. Bauer and Hoye (2014) suggested that wide-ranging predators not only act as energy links between ecosystems, but could also affect local diversity and food web dynamics. The role of mobile marine predators and their habitat connectivity has been generally examined at smaller scales (McCauley et al. 2012a, b; Espinoza et al. 2015a, b; Stehfest et al. 2015; Heupel et al. 2019), so their role enhancing local diversity and food web dynamics remains largely untested. While some studies have provided a good understanding of habitat connectivity and trophic requirements of a species within a system (McCauley et al. 2012a, b), there is still limited information on how mobile link species affect stability and function as they transition between different ecosystems. Based on our findings, we know that populations of large coastal predators such as C. leucas are capable of connecting temperate 13 Marine Biology (2021) 168:80 inshore estuaries and offshore tropical reef habitats at scales of hundreds to thousands of kilometres, potentially transferring nutrients and pathogens, but also increasing ecosystem resilience after disturbance (Lundberg and Moberg 2003; Bauer and Hoye 2014). Network analyses, however, revealed unexplained variation in the seasonal habitat use of males and females tagged at the different arrays. Therefore, a better description of habitat types within the acoustic arrays, as well as prior information on nursery habitats for this species along the coast may increase our understanding of how biological or environmental drivers may shape population structure. Conclusion Animal decisions leading to movement events can be influenced by biological, environmental, and even humaninduced drivers (Rustadbakken et al. 2004; Rittenhouse and Semlitsch 2006; Skov et al. 2011). These drivers do not necessarily act independently, but often in combination, and thus their identification could help predict the timing and duration of individual and/or population level movements (Grayson and Wilbur 2009; Lea et al. 2015). Our findings support the hypothesis that there are seasonal differences in the movement, residency patterns and habitat connectivity of C. leucas across latitudes within the same coastline, further suggesting that intraspecific differences in movement behaviour may be partially explained by large temperature fluctuations in temperate waters, and biological needs such as foraging and reproduction. For large coastal sharks, travelling longer distances to reach a specific reproductive or foraging ground is not only more energetically costly, but could also increase the degree of exposure and spatial overlap with human impacts such as commercial fisheries and bather protection programs (Reid et al. 2011; Taylor et al. 2011; Queiroz et al. 2016; Lee et al. 2018). Conversely, moving long-distances between tropical and temperate ecosystems could also be an evolutionary strategy of this species to maintain genetic diversity and increase connectivity across populations. Intra-specific variation in movement patterns and habitat connectivity can also have important management implications, which is something that should be accounted, particularly when considering management options and identifying the scales of policy for wide-ranging coastal predators. The use of acoustic telemetry and network analyses highlighted the need to better understand seasonal patterns of habitat use and linkages of large wide-ranging predators like C. leucas, as protecting both estuarine and coral reef habitats may be crucial to maintaining reproductive connectivity as well as identifying habitat links that serve as potential foraging grounds and enhancing ecosystem functionality. Marine Biology (2021) 168:80 Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s00227-021-03886-z. Acknowledgements We thank students and staff from the Centre for Sustainable Tropical Fisheries and Aquaculture and staff from NSW Department of Primary Industries, Fisheries Research for their support. Movement data were sourced as part of the Integrated Marine Observing System (IMOS)—IMOS is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS). It is a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent. We are grateful to J. Hazel, L. Couturier, D. Zeh, D. Bowden, CSIRO and UQ for facilitating access to the data from the receiver arrays at LOI, LEI, HI, FI, S and MB. Author contributions ME, AFS, MRH, VMP and CAS designed the study; AFS, MRH, VMP and CAS acquired the funds; ME, EJL, AFS, MRH, VMP, AJT and CAS tagged the sharks; ME and EJL analyzed the data; ME, EJL, AFS, MRH, VMP and CAS prepared the manuscript; ME, EJL, AFS, MRH, VMP and CAS reviewed and edited the manuscript. Funding This project was funded by the Australian Government’s National Environmental Research Program (Tropical Ecosystems Hub Project 6.1) and NSW Department of Primary Industries. MRH was supported by a Future Fellowship (#FT100101004) from the Australian Research Council and ME was supported by the PADI Foundation, internal funding from the College of Marine and Environmental Sciences, Australian Endeavour and AIMS@JCU Scholarships. The project was conducted under research permits from NSW DPI, Fisheries (PO1/0059A-2.0), the Great Barrier Reef Marine Park Authority (G10/33754.1 and G10/33758.1) and animal ethics approvals Ref 07/08-CFC (NSW) and A1933 (QLD). Data availability The datasets generated during and/or analyzed during the current study are available from the Integrated Marine Observing System (IMOS), Animal Tracking Facility database—https://a nimal trac king.aodn.org.au/ Declarations Conflict of interest The authors declare no conflicts of interest. References Bansemer C, Bennett MB (2011) Sex- and maturity-based differences in movement and migration patterns of grey nurse shark, Carcharias taurus, along the eastern coast of Australia. 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