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Article

Capture Response and Long-Term Fate of White Sharks (Carcharodon carcharias) after Release from SMART Drumlines

by
Paul A. Butcher
1,2,*,
Kate A. Lee
3,4,
Craig P. Brand
1,
Christopher R. Gallen
1,
Marcel Green
5,
Amy F. Smoothey
5 and
Victor M. Peddemors
5
1
NSW Department of Primary Industries, Fisheries Research, National Marine Science Centre, Coffs Harbour, NSW 2450, Australia
2
National Marine Science Centre, Southern Cross University, Coffs Harbour, NSW 2450, Australia
3
Sydney Institute of Marine Science, Mosman, NSW 2088, Australia
4
Department of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia
5
NSW Department of Primary Industries, Sydney Institute of Marine Science, Mosman, NSW 2088, Australia
*
Author to whom correspondence should be addressed.
Biology 2023, 12(10), 1329; https://doi.org/10.3390/biology12101329
Submission received: 18 July 2023 / Revised: 13 September 2023 / Accepted: 17 September 2023 / Published: 12 October 2023
(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)
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Abstract

:

Simple Summary

Conflicts between humans and sharks have often been dealt with by catching and killing sharks. However, there is now a growing demand for methods that protect water users from shark bites while minimizing harm to all species. Shark-Management-Alert-in-Real-Time (SMART) drumlines, a new non-lethal shark mitigation method, alert responders when an animal takes the bait, giving them the opportunity to quickly respond. In a study conducted in New South Wales, Australia, 36 White Sharks (Carcharodon carcharias) were caught using SMART drumlines and tagged with satellite-linked radio transmitters (SLRTs) and acoustic tags before being released to examine the short-term post-release movements and longer-term fate of White Sharks after capture, tagging, and release. During the first three days after release, the sharks moved away from the shore and stayed mostly offshore. Although sharks gradually moved closer to the shore 10 days after release, 77% of the sharks remained more than 1.9 km away from the coast and an average of 5 km away from where they were tagged. The sharks were acoustically detected for an average of 591 days after release, with detections ranging from 45 to 1075 days, highlighting longer-term survival. Although five out of the 36 sharks were not detected by the acoustic receivers, the SLRTs indicated that these sharks were alive and well, with detections ranging from 43 to 639 days after release. These findings demonstrate the effectiveness of SMART drumlines as a non-lethal method to mitigate bites by White Sharks.

Abstract

Human-shark conflict has been managed through catch-and-kill policies in most parts of the world. More recently, there has been a greater demand for shark bite mitigation measures to improve protection for water users whilst minimizing harm to non-target and target species, particularly White Sharks (Carcharodon carcharias), given their status as a Threatened, Endangered, or Protected (TEP) species. A new non-lethal shark bite mitigation method, known as the Shark-Management-Alert-in-Real-Time (SMART) drumline, alerts responders when an animal takes the bait and thereby provides an opportunity for rapid response to the catch and potentially to relocate, tag, and release sharks. Thirty-six White Sharks were caught on SMART drumlines in New South Wales, Australia, and tagged with dorsal fin-mounted satellite-linked radio transmitters (SLRTs) and acoustic tags before release. Thirty-one sharks were located within 10 days, 22 of which provided high-quality locations (classes 1 to 3) suitable for analysis. Twenty-seven percent and 59% of these sharks were first detected within 10 and 50 h of release, respectively. For the first three days post-release, sharks moved and mostly remained offshore (>3.5 km from the coast), irrespective of shark sex and length. Thereafter, tagged sharks progressively moved inshore; however, 77% remained more than 1.9 km off the coast and an average of 5 km away from the tagging location, 10 days post-release. Sharks were acoustically detected for an average of 591 days post-release (ranging from 45 to 1075 days). Although five of the 36 sharks were not detected on acoustic receivers, SLRT detections for these five sharks ranged between 43 and 639 days post-release, indicating zero mortality associated with capture. These results highlight the suitability of SMART drumlines as a potential non-lethal shark bite mitigation tool for TEP species such as White Sharks, as they initially move away from the capture site, and thereby this bather protection tool diminishes the immediate risk of shark interactions at that site.

1. Introduction

Globally, shark interactions have increased over the past three decades [1,2,3]. These events are, however, still relatively rare, and the risk of serious injury or death is extremely low compared to the risks associated with other beach activities (e.g., drowning [4]). However, when shark bites occur, they elicit public fear and media attention, generating a level of fear that does not necessarily reflect the true risk [5]. Until recently, the increase in shark bites has been attributed to an increasing human population and, thus, greater participation in water-based activities, particularly surfing [1]. Yet, these factors alone cannot account for the rise. Ryan et al. [2] identified various environmental factors influencing the risk of shark attacks in Australia, including geographical location, sea surface temperature, rainfall, and distance to river mouths, with complex species-specific relationships. Irrespective of the underlying mechanisms contributing to the rise in shark bites, spatial and temporal clusters of interactions in Australia (e.g., [6]) and elsewhere (e.g., Reunion Island [7]; Brazil [8]) result in concern from the public demanding that government agencies enhance shark mitigation strategies to increase safety and awareness [2].
Traditionally, shark mitigation programs have initiated a response that incorporates catch-and-kill measures against a suite of species thought to be responsible for the majority of shark bites (e.g., target sharks of the Bull Shark Carcharhinus leucas, the Tiger Shark Galeocerdo cuvier, and the White Shark Carcharodon carcharias in New South Wales, NSW). In some regions, ongoing shark bite mitigation measures have been in place for decades [9,10]. Traditionally, these programs on the east coast of South Africa and Australia have not released sharks found alive in the fishing gear [11]. The South African program using nets and drumlines initiated a release policy in 1989 [12], followed by the NSW nets and Queensland nets and drumlines programs (2008/09 and 2020, respectively), but no post-release tracking of sharks has been published to determine the survivorship and movements of these sharks.
Traditional gear to mitigate shark bites (shark nets and drumlines) incorporates substantial by-catch of marine mammals, reptiles, rays, and non-target sharks [10,13,14,15], many of which are listed globally as Threatened, Endangered or Protected (TEP) species. Concerns associated with the impacts of shark nets and drumlines on marine wildlife have led to the development and trial of non-lethal bather protection strategies, such as aerial surveillance by helicopters and drones [16,17,18], testing of personal shark deterrent devices [19,20,21,22,23], visual detection [7], sonar technology [24], environmentally friendly physical shark barriers [25], chemical repellents [22,26,27], physical barriers [28,29], land-based observers for shark spotting [30], acoustic deterrents [31,32], and real-time detection of acoustically tagged sharks via in-water receivers [33], that subsequently provide public alerts via social media. Additionally, substantial increases in acoustic tagging of sharks have provided an increased understanding of the ecology of sharks (e.g., Bull Shark [34,35]; Tiger Shark [36]; White Shark [37,38]) in order to advise beach authorities and the public of periods and locations of potentially increased risk. However, differences in opinion do exist in the community around the best options available for use as a bather protection tool [39].
In south-eastern Australia, the majority of shark bites occur in nearshore areas, with a seasonal peak between November and April [1]. Most serious bites in this region are attributed to White, Bull, and Tiger Sharks [3,40], which in NSW are collectively referred to as ‘target sharks’ as they are the focus of shark mitigation measures. Most of these serious or fatal bites were attributed to juvenile and/or sub-adult White Sharks (Australian Shark Incident Database). White Sharks are most commonly distributed throughout sub-tropical and temperate regions [41]. In Australia, they are distributed throughout southern waters, from southern Queensland on the east coast to the North West Cape in Western Australia [42]. Studies on the presence and movements of juvenile and sub-adult (180–320 cm total length—TL) White Sharks have found that they occur mainly in coastal, continental shelf, or slope waters [37,38,43,44,45] with larger sharks using more pelagic environments [46], often aggregating around continental islands [47,48,49]. Along the Australian east coast, juvenile and sub-adult White Sharks have complex patterns of movements with high individual variability, yet exhibit seasonal site fidelity to a few locations [37,44]. Although juvenile and sub-adult White Sharks are present along the east coast year-round, they exhibit higher occupancy in nearshore areas in central and northern NSW from June to November [37,50], which has implications for human-wildlife conflict management.
Following a cluster of shark bites in northern NSW in 2014/2015, the NSW Government established the NSW Shark Management Strategy (SMS), which trialed a suite of new and emerging shark bite mitigation measures with the objective of increasing protection for water users while minimizing harm to target and non-target species (https://www.sharksmart.nsw.gov.au, accessed on 17 July 2023). One of these new shark bite mitigation measures was SMART (Shark-Management-Alert-in-Real-Time) drumlines, which were developed on Réunion Island in 2013 [51]. They are traditional drumlines coupled with a Global Positioning System (GPS) enabled buoy that automatically provides near real-time alerts via satellite communications to the presence of a captured animal via email, phone call, and text message. This enables a rapid response time, reducing the likelihood of injuries or fatalities for the captured animals.
SMART drumline trials in NSW have successfully caught all three target species [52,53]. Catch protocols require responders (scientists or contractors) to attend to captured animals within 30 min to maximize survival. Analysis of blood physiology from White Sharks caught on SMART drumlines indicates that the capture process is relatively benign and that the response times in NSW are appropriate to minimize long-term negative impacts on released White Sharks [52,54]. However, one of the concerns of stakeholders is that sharks released from SMART drumlines may remain inshore post-release, effectively negating the shark bite mitigation measure. The primary aim of this study is to quantify the short-term post-release movements and the longer-term fate of White Sharks after capture, tagging, and release from SMART drumlines. This study will provide critical information to support the utility of this process as a non-lethal bather protection tool.

2. Materials and Methods

Between May and October 2016, White Sharks were captured on SMART drumlines deployed off the east coast of NSW, Australia, at Ballina (−28.8 S 153.6 E), Evans Head (−29.1 S 153.4 E), Coffs Harbour (−30.3 S 153.2 E), Crowdy Head (−31.8 S 152.7 E), and Tuncurry (−32.2 S 152.5 E, Figure 1).
On each fishing day, SMART drumlines were deployed during daylight hours ~500 m from shore, following the same configuration used in Tate et al. [52] and Gallagher et al. [54]. Once an alert of capture was received via phone call, text message, and email, a research vessel traveled to the SMART drumline. When the SMART drumline was retrieved, the trace was immediately attached to a longer rope so the shark could be secured to the side of the vessel using an additional cross-pectoral fin rope to support the body and a tail harness, thereby minimizing potential injuries associated with pressure or crushing. Each shark was secured within five minutes of its arrival.
Data collected included biological data of sex and lengths (precaudal—PCL, fork—FL, and total—TL to the nearest cm), technical parameters of time of capture and release (h:m), and release location coordinates. All sharks were tagged with dorsal fin-mounted satellite-linked radio transmitting (SLRT) tags following the methods of Bruce and Bradford [44]. These tags transmit the shark’s position to the Advanced Research and Global Observation Satellites (ARGOS) system whenever the dorsal fin breaks the surface of the water. These positions are classified on a scale of decreasing accuracy using seven location classes of 3, 2, 1, 0, A, B, and Z, with class 3 being the most accurate with an error of <250 m, class 2 of 250–500 m, and class 1 of 500–1500 m. Location classes 0 to B provide estimates > 1500 m, while class Z indicates no position [55].
Each shark was also tagged with a uniquely numbered identification tag (spaghetti tag, Hallprint, South Australia) to enable individual identification if they were recaptured by other fishers. These tags were inserted into the musculature at the base of the first dorsal fin. As part of a larger research project, acoustic transmitters with transmission intervals of 40–80 s and a 10-year battery life were surgically implanted into the abdominal cavity following the general procedure described by Bruce and Bradford [48]. These tags were monitored by an array of 21 Iridium satellite-linked acoustic receivers, which effectively detect tagged sharks in near real-time ([33,56] Vemco VR4-Global—“tagged shark listening station”). These tagged shark listening stations were deployed 500 m from shore in 8–16 m of water, with the hydrophone 4 m below the surface. They are designed to detect tagged sharks in the vicinity of up to 400–500 m [57], but shorter-range limits of 150 to 300 m have also been observed [33,50].

Statistical Analysis

Only satellite detections with location classes of 1 to 3 were included in the analyses (i.e., classes A, B, Z, and 0 were excluded), so that all the locations had a maximum error radius of <1500 m. All locations were reprojected to an equal-area projection system (GDA 94/Australian Albers; EPSG: 3576).
A shapefile of the coastline of Australia was downloaded from the Geoscience Australia data repository (https://data.gov.au/dataset/geodata-coast-100k-2004, accessed on 17 July 2023). Data were derived from a 1:100,000 scale topographic map, and coastline features were defined from the mean high-water mark. This shapefile was reprojected into the same datum as the satellite tag locations. The ‘near’ tool in ArcGIS 10.5 (Environmental Systems Research Institute (ESRI), Redlands, CA, USA) was used to calculate the distance from (i) the coast for each of the locations for the first ten days post-tagging and (ii) the post-tagging release location to the first detection. The Geodesic method was used for both, as this accounts for the curvature of the earth to correctly measure the distance between two features. The location of the VR4G acoustic receivers was used as the shark location for all locations from acoustic tags.
A mixed effects model was used to test if the sex, size (total length—cm), or time since release (in days) influenced the distance from the coast that each shark was detected following tagging. The response variable (distance from the coast) was positively skewed, so it wasn’t appropriate to use a linear model. Mixed models were used to account for the repeated measurements on individual sharks (with the unique shark tag code used as a random effect). A Generalised Additive Mixed Model (GAMM) and a generalized linear mixed model (GLMM) with a Gamma link function were tested, and the GLMM had the lowest Akaike information criterion corrected for sample size (AICc), so it was used for subsequent modeling. The GAMM was implemented using the mgcv package [58] and the GLMM using the lme4 package [59] in R [60]. Generalized variance inflation factors (VIF) were checked for collinearity between the explanatory variables. All variables had a VIF of <3 [61] and were assumed to not be collinear. The inclusion of the variables in the “best” model was based on AICc. All models with an AICc of <10 were averaged using the MuMIn [62] package in R, and permutations with each possible combination of variables, including the null model, were tested. The relative importance of each variable was calculated as the sum of the AICc weights over all the models in which it was included. Model adequacy was checked using standard residual plots (Figure S1—Supplementary Materials).

3. Results

Thirty-six White Sharks, comprising 19 females (mean ± SD of 265 ± 52 cm TL, 172–367 cm TL) and 17 males (256 ± 39 cm TL, 213–306 cm TL), were caught on SMART drumlines, tagged, and released. Sharks were released 34–121 min (mean 56.7 ± 15.0 min) post-hooking, with an elapsed time (mean and range) from when each shark was secured at the boat to release of 31.8 ± 8.2 min (range of 19–40 min, Table 1). All sharks were detected post-release. SLRT tags reported positions for an average of 348 ± 47 days (range 4–1061), while acoustic tags were detected for an average of 591 ± 59 days (range 45–1075 days, Table 1).
Thirty-one sharks had satellite detections within ten days of release (including all location classes); however, only 22 sharks had locations with classes 1 to 3 (Table 1). The average time until first detection for all 22 sharks was 61 h after tagging, 34.3 km (range of 6.8 to 107.9 km) from their tagging location, and 12.4 km (range of 2.6 to 36.2 km) offshore (Table 1; Figure 1). Twenty-seven percent of sharks were first detected within 10 h post-release, while 59% were detected within 50 h (Figure 2a,b). For the first three days post-release, sharks moved and mostly remained offshore (>3.5 km from the coast). Thereafter, there was considerable variability in the distribution of their offshore distance. However, while the SLRT tags showed that most sharks remained further than 1.9 km from the coast during the first 10 days (Figure 3 and Figure 4), the SLRT tag of one shark indicated it was within 500 m of shore and 5 km from the release site 20 h after tagging. Four sharks were first detected by the tagged shark listening stations in nearshore waters via their acoustic tags. These comprised two sharks detected after 4 days (25 and 45 km away) and two sharks detected after 6 days (0 and 86 km away) (Table 1). The average (± SD) distance from the release site for these four acoustically detected sharks was 27.4 ± 25.7 km.
Only five of the 36 acoustically tagged sharks were not detected on any of the 21 tagged shark listening stations across the 1324 to 1461-day post-release period (Table 1). For the remaining 31 sharks, the average time to first detection on one of the 21 tagged shark listening stations was 127.4 ± 31.6 days (range of 4 to 605). All animals were on average 124.6 ± 22.3 km away from the release site at their first detection on a tagged shark listening station (range of 0 to 413 km).
Four sharks were detected relatively shortly after release at the same location as their release (Table 1). Three of these were at Sharpes Beach, Ballina, with one detected six days after release and two sharks detected 28 days after release. The latter two sharks were tagged together and then detected on the same day back at the beach where they were tagged. Another shark was caught and first detected at the same release location at Forster 56 days after the initial release.
Model selection for a GLMM produced eight candidate models with an AICc of <10 (Table 2). Relative importance was low for all the explanatory variables, with each variable only included in half of the top models. None of the explanatory variables were essential predictors for the distance from the coast where sharks were located within the first 10 days post-tagging, with sex (0.31), total length (0.30), and time since tagging (0.29) being the most important variables. There was a slightly positive relationship between time since release and distance offshore, with females and smaller sharks more likely to remain closer to the coast than males or larger sharks. However, the overall influence of these predictors was weak (Figure 5).

4. Discussion

This is the first study to quantify the short-term movement and longer-term survival of White Sharks after catch and release from SMART drumlines. Post release, White Sharks moved offshore before moving back to the nearshore coastline. While SMART drumlines are a useful tool for catching White Sharks by intercepting them before they can interact with water users, their offshore movement after release provides a means of minimizing further shark-human interactions by those individuals in that area in the short term. The potential benefits that SMART drumlines offer for reducing shark-human interactions are discussed below by considering the movement and longer-term survival of White Sharks after release. Although White Sharks are a globally targeted species for shark bite mitigation measures, they are also protected throughout much of their range [63] and, as such, a process whereby White Sharks are removed from an area of potential human-wildlife conflict with no long-term harm to the animal is desired [64]. Our results indicate that rapid response to SMART drumline captures of White Sharks can deliver this outcome.
All White Sharks were detected post-release, either through their SLRT or acoustic tags. The distance from the release site to the first detection indicates that the sharks actively swam away after release. All sharks swam offshore once released, a behavioral post-release response to capture that is well documented for other shark species such as Dusky Shark (Carcharhinus obscurus) and Sandbar Shark (Carcharhinus plumbeus) [65]. When used in isolation, the SLRT tags showed that most sharks remained offshore (>3.5 km from the coast) for an average of three days before slowly making their way back to shore.
Using animal-borne cameras incorporating multi-sensor biologging tags, Grainger et al. [66] monitored the fine-scale short-term behavioral responses of White Sharks to SMART drumline capture and estimated the longevity of the impact on the natural behavior of White Sharks as defined by changes in swimming speed. These analyses indicate that White Sharks released from SMART drumlines recovered to exhibit non-disturbed behavior and tail-beat rates within 10 h post-release. These findings also corroborate those of Tate et al. [52] who showed the capture process associated with SMART drumlines to be relatively benign on the short-term physiological status of White Sharks under the current response times. Acoustic detections and recaptures of White Sharks caught by SMART drumlines and other fishing gear, years after initial capture and tagging, also demonstrate little or no physiological impact in the medium to longer term.
The speed of movement post-release varied among individuals, yet most individuals moved relatively fast and generally offshore. Some individuals were detected up to 40 km offshore from the release site in the first 24 h post-release. Average swimming speeds of 0.8 m s−1 have been documented in White Sharks off eastern Australia using drones [67] and SLRT tags [38]. These swimming speeds are lower than those recorded elsewhere (>1.31 m s−1, [68]; average 0.94 m s−1, [69]) and may represent slower nearshore movements. As swim speeds of up to 10 m s−1 have been recorded when White Sharks are near potential prey, such as seal colonies [70] and schools of fish [67], it is extremely plausible that post-released sharks are moving more rapidly when heading offshore and could easily move 40 km in 24 h.
Although the explanatory variables investigated in this study were not key predictors for the distance from the coast where sharks were located within the first 10 days post-tagging, female and smaller White Sharks were most likely to return inshore during this period. Previous studies have also indicated a tendency for females to favor inshore habitats, with an inclination among immature male White Sharks towards large-scale migrations [37,38,71]. There were also significant positive relationships between time after release and the likelihood of White Sharks being found further from the coast.
The size (total length) of the shark affected distance to the coast at 10 days post-release, implying that larger sharks were continuing long-shore movements in deeper water. Bruce and Bradford [44] hypothesize that juvenile White Sharks utilize a ‘depth corridor’ (between 60 and 120 m isobaths) when traveling along the coast, which supports the hypothesis that larger sharks may stay further offshore and continue with long-shore movements for longer than the smaller sharks that seek out nearshore habitat sooner. Coxon et al. [46] confirm an apparent preference for offshore habitats by large (340 to 380 cm TL) White Sharks off eastern Australia. Similarly, the inshore bias towards female White Sharks reported by Bruce et al. [37] and Spaet et al. [50], plus those individuals observed in more historical shark control programs along eastern Australia [72,73,74] and more recently in the monthly NSW SMART drumline catch reports (1.53 females: 1 male) (https://www.sharksmart.nsw.gov.au/technology-trials-and-research/smart-drumlines/ accessed on 1 June 2023) suggests that female White Sharks are more likely to be found within nearshore waters off the east Australian coast. Subsequently, they are more likely to move back inshore into their apparent preferred habitat.
Previous research has shown that White Sharks undergo regular long-distance movements [56,74,75,76,77]. Further, individuals exhibit site fidelity at various stages of their travels, particularly juvenile sharks, which regularly visit important nearshore areas. Along the eastern coast of Australia, at least two nursery areas have been recognized [37,38,43,73]. This site fidelity will inevitably lead to juvenile and sub-adult sharks returning to the original site of capture; however, our results suggest that an immediate post-release return to beaches where human-wildlife conflict is being mitigated is unlikely. The results therefore support the use of capture and offshore release of live sharks as a low-impact shark bite mitigation measure, i.e., that SMART drumlines meet the dual objectives of increasing protection for beachgoers from sharks while simultaneously minimizing harm to sharks (and other marine life).
The rapid response coupled with careful and timely handling of White Sharks caught on SMART drumlines has led to their successful release, with sharks showing little physiological response to the capture experience [52,53,54] and all sharks subsequently being detected via telemetry. Although one shark never reported via its satellite tag and another three SLRT tags stopped emitting within a month, the 8% failure rate of these tags is well within the failure range reported previously [37]. Complementary tagging of these satellite-tracked sharks using acoustic tags confirmed that none succumbed to capture stress, as sharks carrying satellite tags that appeared to fail were all acoustically detected a minimum of 74 days post-release. The observed survival of all sharks supports their resilience to the catch, tag, and release process under the response times and handling procedures reported here. These results provide comprehensive information on the long-term fate of White Sharks, illustrating the utility of using SMART drumlines as a bather protection tool with little or no impact on its primary target species.

5. Conclusions

White Sharks are the species most implicated in shark bites in Australia, and their seasonal occurrence in nearshore areas of NSW has implications for human-wildlife conflict management. By using satellite and acoustic tagging technologies to monitor the post-release movements of White Sharks caught on SMART drumlines, we have shown that most White Sharks move away from the capture site, thereby reducing the likelihood of shark-human interactions at that site. Furthermore, the survival of White Sharks highlights the efficacy of SMART drumlines as a potential non-lethal shark bite mitigation tool for a Threatened, Endangered, or Protected species.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/biology12101329/s1, Figure S1: Standard residual plot showing the results of model adequacy.

Author Contributions

Conceptualization, P.A.B.; methodology, P.A.B., A.F.S. and V.M.P.; validation, P.A.B., K.A.L., A.F.S. and V.M.P.; formal analysis, K.A.L. and P.A.B.; investigation, K.A.L. and P.A.B.; resources, P.A.B. and M.G.; data curation, P.A.B., K.A.L., C.R.G. and C.P.B.; writing—original draft preparation, P.A.B., A.F.S., K.A.L., M.G. and V.M.P.; writing—review and editing, P.A.B., K.A.L., M.G., A.F.S. and V.M.P.; project administration, P.A.B.; funding acquisition, M.G. All authors have read and agreed to the published version of the manuscript.

Funding

Primary project funding and support were provided by the New South Wales Department of Primary Industries, Australia through the Shark Management Strategy.

Institutional Review Board Statement

This study was done under New South Wales Department of Primary Industries Scientific Research Section 37 (Ref. P01/0059A-2.0), Marine Parks (Ref. P16/0145-1.1), and Animal Care and Ethics (ACEC Ref. 07/08) permits.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data for this project are maintained by the New South Wales Government. The data is available upon request.

Acknowledgments

This project would not have been possible without the continued support of our research, management, and SMART drumline teams.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. West, J.G. Changing patterns of shark attacks in Australian waters. Mar. Freshw. Res. 2011, 62, 744–754. [Google Scholar] [CrossRef]
  2. Curtis, T.; Bruce, B.; Cliff, G.; Dudley, S.; Klimley, A.; Kock, A.; Lea, R.; Lowe, C.; McCosker, J.; Skomal, G.; et al. Responding to the risk of white shark attack: Updated statistics, prevention, control methods, and recommendations. In Global Perspectives on the Biology and Life History of the Great White Shark; Domeier, M.L., Ed.; CRC Press: Boca Raton, FL, USA, 2012; pp. 477–510. [Google Scholar]
  3. Ryan, L.A.; Lynch, S.K.; Harcourt, R.; Slip, D.J.; Peddemors, V.; Everett, J.D.; Harrison, L.M.; Hart, N.S. Environmental predictive models for shark attacks in Australian waters. Mar. Ecol. Prog. Ser. 2019, 631, 165–179. [Google Scholar] [CrossRef]
  4. Crossley, R.; Collins, C.M.; Sutton, S.G.; Huveneers, C. Public perception and understanding of shark attack mitigation measures in Australia. Hum. Dimens. Wildl. 2014, 19, 154–165. [Google Scholar] [CrossRef]
  5. Muter, B.A.; Gore, M.L.; Gledhill, K.S.; Lamont, C.; Huveneers, C. Australian and US news media portrayal of sharks and their conservation. Conser. Biol. 2013, 27, 187–196. [Google Scholar] [CrossRef] [PubMed]
  6. Barnett, A.; Fitzpatrick, R.; Bradley, M.; Miller, I.; Sheaves, M.; Chin, A.; Smith, B.; Diedrich, A.; Yick, J.L.; Lubitz, N.; et al. Scientific Response to a Cluster of Shark Bites. People Nat. 2022, 4, 963–982. [Google Scholar]
  7. Lagabrielle, E.; Allibert, A.; Kiszka, J.J.; Louiseau, N.; Kilfoil, J.P.; Lemahieu, A. Environmental and anthropogenic factors affecting the increasing occurrence of shark-human interactions around a fast-developing Indian Ocean island. Sci. Rep. 2018, 8, 3676. [Google Scholar] [CrossRef]
  8. Hazin, F.H.V.; Burgess, G.; Carvalho, F.C. A shark attack outbreak off Recife, Pernambuco, Brazil: 1992–2006. Bull. Mar. Sci. 2008, 82, 199–212. [Google Scholar]
  9. Dudley, S.F.J. A comparison of the shark control programs of New South Wales and Queensland (Australia) and KwaZulu-Natal (South Africa). Ocean. Coast. Manag. 1997, 34, 1–27. [Google Scholar] [CrossRef]
  10. Reid, D.D.; Robbins, W.D.; Peddemors, V.M. Decadal trends in shark catches and effort from the New South Wales, Australia, Shark Meshing Program 1950–2010. Mar. Freshw. Res. 2011, 62, 676–693. [Google Scholar] [CrossRef]
  11. Cliff, G.; Dudley, S.F.J. Reducing the environmental impact of shark-control programs: A case study from KwaZulu-Natal, South Africa. Mar. Freshw. Res. 2011, 62, 700–709. [Google Scholar] [CrossRef]
  12. Cliff, G. Shark attacks on the South African coast between 1960 and 1990. S. Afr. J. Sci. 1991, 87, 513–518. [Google Scholar]
  13. Dudley, S.F.J.; Cliff, G. Sharks caught in the protective gill nets off Natal, South Africa. 7. The blacktip shark Carcharhinus limbatus (Valenciennes). S. Afr. J. Mar. Sci. 1993, 13, 237–254. [Google Scholar] [CrossRef]
  14. Krogh, M.; Reid, D. Bycatch in the protective shark meshing program off south-eastern New South Wales, Australia. Biol. Conser. 1996, 77, 219–226. [Google Scholar] [CrossRef]
  15. Sumpton, W.D.; Taylor, S.M.; Gribble, N.A.; McPherson, G.; Ham, T. Gear selectivity of large-mesh nets and drumlines used to catch sharks in the Queensland Shark Control Program. S. Afr. J. Mar. Sci. 2011, 33, 37–43. [Google Scholar] [CrossRef]
  16. Robbins, W.D.; Peddemors, V.M.; Kennelly, S.J.; Ives, M.C. Experimental evaluation of shark detection rates by aerial observers. PLoS ONE 2014, 9, e83456. [Google Scholar] [CrossRef] [PubMed]
  17. Colefax, A.P.; Butcher, P.A.; Kelaher, B.P. The potential for unmanned aerial vehicles (UAVs) to conduct marine fauna surveys in place of manned aircraft. ICES J. Mar. Sci. 2018, 75, 1–8. [Google Scholar] [CrossRef]
  18. Butcher, P.A.; Piddocke, T.P.; Colefax, A.P.; Hoade, B.; Peddemors, V.M.; Borg, L.; Cullis, B.R. Beach safety: Can drones provide a platform for sighting sharks? Wildli. Res. 2019, 46, 701–712. [Google Scholar] [CrossRef]
  19. Smit, C.F.; Peddemors, V. Estimating the probability of a shark attack when using an electrical repellent. S. Afr. Stat. J. 2003, 37, 59–78. [Google Scholar]
  20. Huveneers, C.; Rogers, P.J.; Semmens, J.; Beckmann, C.; Kock, A.A.; Page, B.; Goldsworthy, S.D. Effects of an electric field on white sharks: In situ testing of an electric deterrent. PLoS ONE 2013, 8, e62730. [Google Scholar] [CrossRef]
  21. Huveneers, C.; Whitmarsh, S.; Thiele, M.; Meyer, L.; Fox, A.; Bradshaw, C.J.A. Effectiveness of five personal shark-bite deterrents for surfers. PeerJ 2018, 6, e5554. [Google Scholar] [CrossRef]
  22. Hart, N.S.; Collin, S.P. Shark senses and shark repellents. Int. Zool. 2015, 10, 38–64. [Google Scholar] [CrossRef] [PubMed]
  23. Blount, C.; Pygas, D.; Lincoln Smith, M.P.; McPhee, D.P.; Bignell, C.; Ramsey, O. Effectiveness Against White Sharks of the Rpela Personal Shark Deterrent Device Designed for Surfers. J. Mar. Sci. Technol. 2021, 29, 13. [Google Scholar] [CrossRef]
  24. Parsons, M.; Parnum, I.; Allen, K.; McCauley, R.; Erbe, C. Detection of sharks with the Gemini imaging sonar. Acoust. Aust. 2014, 42, 185–189. [Google Scholar]
  25. O’Connell, C.P.; Andreotti, S.; Rutzen, M.; Meӱer, M.; Matthee, C.A. Testing the exclusion capabilities and durability of the Sharksafe Barrier to determine its viability as an eco-friendly alternative to current shark culling methodologies. Aqu. Conserv. Mar. Freshw. Ecosyst. 2018, 28, 252–258. [Google Scholar] [CrossRef]
  26. Stroud, E.M.; O’Connell, C.P.; Rice, P.H.; Snow, N.; Barnes, B.B.; Hanson, J.E. Existence of a shark necromone derived from putrefied shark tissue. Oce. Coa. Manag. 2014, 97, 50–57. [Google Scholar]
  27. Broadhurst, M.K.; Tolhurst, D.J. Null effects of decomposing shark issue on baited-hook catches of elasmobranchs. Reg. Stud. Mar. 2021, 46, 10898. [Google Scholar]
  28. Davison, A.; Kock, A. Fish Hoek Exclusion Net Evaluation Report; Shark Spotter Report; Shark Spotters: Cape Town, South Africa, 2014; Available online: https://sharkspotters.org.za/wp-content/uploads/2016/10/FINAL-Exclusion-net-report-24-06-14.pdf (accessed on 1 April 2023).
  29. O’Connell, C.; Crews, J.; King, A.; Gressle, J. Evaluating the shark deterrent effects of the novel exclusion barrier in comparison to the rigorously tested sharksafe barrier technology. J. Mar. Sci. Eng. 2022, 10, 634. [Google Scholar] [CrossRef]
  30. Engelbrecht, T.; Kock, A.; Waries, S.; O’Riain, M.J. Shark Spotters: Successfully reducing spatial overlap between white sharks (Charcharodon carcharias) and recreational water users in False Bay, South Africa. PLoS ONE 2017, 12, e0185335. [Google Scholar] [CrossRef]
  31. Chapuis, L.; Collin, S.P.; Yopak, K.E.; McCauley, R.D.; Kempster, R.M.; Ryan, L.A.; Schmidt, C.; Kerr, C.C.; Gennari, E.; Egeberg, C.A.; et al. The effect of underwater sounds on shark behaviour. Sci. Rep. 2019, 9, 6924. [Google Scholar] [CrossRef]
  32. Ryan, L.A.; Chapuis, L.; Hemmi, J.M.; Collin, S.P.; McCauley, R.D.; Yopak, K.E.; Gennari, E.; Huveneers, C.; Kempster, R.M.; Kerr, C.C.; et al. Effects of auditory and visual stimuli on shark feeding behaviour: The disco effect. Mar. Biol. 2018, 165, 11. [Google Scholar] [CrossRef]
  33. Bradford, R.W.; Bruce, B.D.; McAuley, R.B.; Robinson, G. An evaluation of passive acoustic monitoring using satellite communication technology for near real-time detection of tagged animals in a marine setting. Open Fish Sci. J. 2011, 4, 10–20. [Google Scholar] [CrossRef]
  34. Lee, K.A.; Smoothey, A.F.; Harcourt, R.G.; Roughan, M.; Butcher, P.A.; Peddemors, V.M. Environmental drivers of abundance and residency of a large migratory shark, Carcharhinus leucas, inshore of a dynamic western boundary current. Mar. Ecol. Prog. Ser. 2019, 622, 121–137. [Google Scholar] [CrossRef]
  35. Smoothey, A.F.; Lee, K.A.; Peddemors, V.M. Long-term patterns of abundance, residency and movements of bull sharks (Carcharhinus leucas) in Sydney Harbour, Australia. Sci. Rep. 2019, 9, 18864. [Google Scholar] [CrossRef] [PubMed]
  36. Niella, Y.; Butcher, P.; Holmes, B.; Barnett, A.; Harcourt, R. Forecasting intraspecific changes in distribution of a wide-ranging marine predator under climate change. Oecologia 2022, 198, 111–124. [Google Scholar] [CrossRef] [PubMed]
  37. Bruce, B.D.; Harasti, D.; Lee, K.; Gallen, C.; Bradford, R. Broad-scale movements of juvenile white sharks Carcharodon carcharias in eastern Australia from acoustic and satellite telemetry. Mar. Ecol. Prog. Ser. 2019, 619, 1–15. [Google Scholar] [CrossRef]
  38. Spaet, J.; Patterson, T.; Bradford, R.; Butcher, P. Spatiotemporal distribution patterns of immature Australasian white sharks (Carcharodon carcharias). Sci. Rep. 2020, 10, 10169. [Google Scholar] [CrossRef] [PubMed]
  39. Martin, C.L.; Curley, B.; Wolfenden, K.; Green, M.; Moltschaniwskyj, N.A. The Social Dimension to the New South Wales Shark Management Strategy, 2015–2020, Australia: Lessons learned. Mar. Pol. 2022, 141, 105079. [Google Scholar] [CrossRef]
  40. McPhee, D. Unprovoked shark bites: Are they becoming more prevalent? Coast. Manage. 2014, 42, 478–492. [Google Scholar] [CrossRef]
  41. Compagno, L.J.V. Sharks of the World. An Annotated and Illustrated Catalogue of Shark Species in Date; FAO: Rome, Italy, 2001; pp. 1–269. [Google Scholar]
  42. Last, P.R.; Stevens, J.D. Sharks and Rays of Australia; CSIRO: Collingwood, Australia, 2009; p. 656. [Google Scholar]
  43. Bruce, B.D.; Stevens, J.D.; Malcolm, H. Movements and swimming behaviour of white Sharks (Carcharodon carcharias) in Australian waters. Mar. Biol. 2006, 150, 161–172. [Google Scholar] [CrossRef]
  44. Bruce, B.D.; Bradford, R.W. Habitat use and spatial dynamics of juvenile white sharks, Carcharodon carcharias, in eastern Australia. In Global Perspectives on the Biology and Life History of the White Shark; Domeier, M.L., Ed.; CRC Press: Boca Raton, FL, USA, 2012; pp. 225–254. [Google Scholar]
  45. Spaet, J.L.Y.; Butcher, P.A.; Manica, A.; Lam, C.H. Spatial dynamics and fine-scale vertical behaviour of immature eastern Australian white sharks. Biology 2022, 11, 1689. [Google Scholar] [CrossRef]
  46. Coxon, J.L.; Butcher, P.A.; Spaet, J.L.Y.; Rizzari, J.R. Preliminary data about habitat use of subadult and adult white sharks (Carcharodon carcharias) in eastern Australian waters. Biology 2022, 11, 1443. [Google Scholar] [CrossRef] [PubMed]
  47. Robbins, R.; Booth, D. Seasonal, sexual and size segregation of White sharks, Carcharodon carcharias, at the Neptune Islands, South Australia. In Global Perspectives on the Biology and Life History of the White Shark; Domeier, M.L., Ed.; CRC Press: Boca Raton, FL, USA, 2012; pp. 225–254. [Google Scholar]
  48. Bruce, B.D.; Bradford, R.W. The effects of shark cage-diving operations on the behaviour and movements of white sharks, Carcharodon carcharias, at the Neptune Islands, South Australia. Mar. Biol. 2013, 160, 889–907. [Google Scholar] [CrossRef]
  49. Bruce, B.D.; Bradford, R. Segregation or aggregation? Sex-specific patterns in the seasonal occurrence of white sharks Carcharodon carcharias at the Neptune Islands, South Australia. J. Fish Biol. 2015, 87, 1355–1370. [Google Scholar] [CrossRef] [PubMed]
  50. Spaet, J.L.Y.; Manica, A.; Brand, C.P.; Gallen, C.; Butcher, P.A. Environmental conditions are poor predictors of immature white shark Carcharodon carcharias occurrences on coastal beaches of eastern Australia. Mar. Ecol. Prog. Ser. 2020, 653, 167–179. [Google Scholar] [CrossRef]
  51. Guyomard, D.; Perry, C.; Tournoux, P.U.; Cliff, G.; Peddemors, V.; Jaquemet, S.J.F.R. An innovative fishing gear to enhance the release of non-target species in coastal shark-control programs: The SMART (shark management alert in real-time) drumline. Fish. Res. 2019, 216, 6–17. [Google Scholar] [CrossRef]
  52. Tate, R.D.; Cullis, B.R.; Smith, S.D.A.; Kelaher, B.P.; Brand, C.P.; Gallen, C.R.; Mandelman, J.W.; Butcher, P.A. The acute physiological status of white sharks (Carcharodon carcharias) exhibits minimal variation after capture on SMART drumlines. Conserv. Physiol. 2019, 7, 1–9. [Google Scholar]
  53. Lipscombe, R.S.; Scott, A.; Morris, S.; Peddemors, V.M.; Smoothey, A.F.; Butcher, P.A. The influence of bait position on the catch of target and non-target sharks in a SMART drumline bather protection program. Fish. Res. 2023, 257, 106501. [Google Scholar] [CrossRef]
  54. Gallagher, A.J.; Meyer, L.; Pethybridge, H.R.; Huveneers, C.; Butcher, P.A. Effects of short-term capture on the physiology of white sharks Carcharodon carcharias: Amino acids and fatty acids. Endanger. Species Res. 2019, 40, 297–308. [Google Scholar] [CrossRef]
  55. CLS. 2011. Argos User’s Manual. Available online: http://www.argos-system.org (accessed on 1 May 2023).
  56. McAuley, R.B.; Bruce, B.D.; Keay, I.S.; Mountford, S.; Pinnell, T.; Whoriskey, F.G. Broad-scale coastal movements of white sharks off Western Australia described by passive acoustic telemetry data. Mar. Freshw. Res. 2017, 68, 1518–1531. [Google Scholar] [CrossRef]
  57. McAuley, R.; Bruce, B.; Keay, I.; Mountford, S.; Pinnell, T. Evaluation of Passive Acoustic Telemetry Approaches for Monitoring and Mitigating Shark Hazards Off the Coast of Western Australia; Department of Fisheries, Government of Western Australia: Joondalup, Australia, 2016.
  58. Wood, S. Generalized Additive Models: An Introduction with R; CRC Press: Boca Raton, FL, USA, 2017. [Google Scholar]
  59. Bates, D.; Mächler, M.; Bolker, B.; Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 2015, 67, 1–48. [Google Scholar] [CrossRef]
  60. R Core Development Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2022; Available online: https://www.R-project.org/ (accessed on 1 May 2023).
  61. Zuur, A.F.; Ieno, E.N.; Elphick, C.S. A protocol for data exploration to avoid common statistical problems. Meth. Ecol. Evol. 2010, 1, 3–14. [Google Scholar] [CrossRef]
  62. Bartoń, K. Mumin: Multi-Model Inference. R Package Version 1.15.6. Available online: https://cran.R-project.Org/package=mumin (accessed on 1 May 2023).
  63. Rigby, C.L.; Barreto, R.; Carlson, J.; Fernando, D.; Fordham, S.; Francis, M.P.; Herman, K.; Jabado, R.W.; Jones, G.C.A.; Liu, K.M.; et al. Carcharodon carcharias (amended version of 2019 assessment). In The IUCN Red List of Threatened Species; International Union for Conservation of Nature and Natural Resources: Cambridge, UK, 2022; p. e.T3855A212629880. [Google Scholar]
  64. Niella, Y.; Peddemors, V.M.; Smoothey, A.F.; Green, M.; Harcourt, R. A “wicked problem” reconciling human-shark conflict, lethal shark control and endangered species. Fron. Cons. Sci. 2021, 2, 720–741. [Google Scholar]
  65. Barnes, C.; Butcher, P.; Peddemors, V.; Mandleman, J. Movements and mortality of two commercially exploited carcharhinid sharks following longline capture and release off eastern Australia. End Spec. Res. 2016, 30, 193–208. [Google Scholar] [CrossRef]
  66. Grainger, R.; Raubenheimer, D.; Peddemors, V.M.; Butcher, P.A.; Machovsky-Capuska, G.E. Integrating biologging and behavioural state modelling to identify cryptic behaviours and post-capture recovery processes: New insights from a threatened marine apex predator. Front. Mar. Sci. 2022, 8, 791185. [Google Scholar] [CrossRef]
  67. Colefax, A.P.; Kelaher, B.P.; Pagendam, D.E.; Butcher, P.A. Assessing white shark (Carcharodon carcharias) behaviour along coastal beaches for conservation-focused shark mitigation. Front. Mar. Sci. 2020, 7, 268. [Google Scholar] [CrossRef]
  68. Bonfil, R.; Meӱer, M.; Scholl, M.C.; Johnson, R.; O’Brien, S.; Oosthuizen, H.; Swanson, S.; Kotze, D.; Paterson, M. Transoceanic migration, spatial dynamics, and population linkages of white sharks. Science 2005, 310, 100–103. [Google Scholar] [CrossRef]
  69. Watanabe, Y.Y.; Payne, N.L.; Semmens, J.M.; Fox, A.; Huveneers, C. Swimming strategies and energetics of endothermic white sharks during foraging. J. Exp. Biol. 2019, 222, 185603. [Google Scholar] [CrossRef]
  70. Semmens, J.M.; Payne, N.L.; Huveneers, C.; Sims, D.W.; Bruce, B.D. Feeding requirements of White sharks may be higher than originally thought. Sci. Rep. 2013, 3, 1471. [Google Scholar] [CrossRef]
  71. Harasti, D.; Lee, K.; Bruce, B.; Gallen, C.; Bradford, R. Juvenile White sharks Carcharodon carcharias use estuarine environments in south-eastern Australia. Mar. Biol. 2017, 164, 58. [Google Scholar] [CrossRef]
  72. Lee, K.A.; Roughan, M.; Harcourt, R.G.; Peddemors, V.M. Environmental correlates of relative abundance of potentially dangerous sharks in nearshore areas, southeastern Australia. Mar. Ecol. Prog. Ser. 2018, 599, 157–179. [Google Scholar] [CrossRef]
  73. Werry, J.M.; Bruce, B.D.; Sumpton, W.; Reid, D.; Mayer, D.G. Beach areas used by juvenile White shark, Carcharodon carcharias, in eastern Australia. In Global Perspectives on the Biology and Life History of the White Shark; Domeier, M.L., Ed.; CRC Press: Boca Raton, FL, USA, 2012; pp. 225–254. [Google Scholar]
  74. Domeier, M.L.; Nasby-Lucas, N. Two-year migration of adult female white sharks (Carcharodon carcharias) reveals widely separated nursery areas and conservation concerns. Anim. Biotele. 2013, 1, 2. [Google Scholar] [CrossRef]
  75. Jorgensen, S.J.; Reeb, C.A.; Chapple, T.K.; Anderson, S.; Perle, C.; Van Sommeran, S.R.; Fritz-Cope, C.; Brown, A.C.; Klimley, A.P.; Block, B.A. Philopatry and migration of Pacific white sharks. Proc. R. Soc. B. 2009, 277, 1155. [Google Scholar] [CrossRef] [PubMed]
  76. Kock, A.C.; Photopoulou, T.; Durbach, I.; Mauff, K.; Meӱer, M.; Kotze, D.; Griffiths, C.L.; O’Riain, M.J. Summer at the beach: Spatio-temporal patterns of white shark occurrence along the inshore areas of False Bay, South Africa. Mov. Ecol. 2018, 6, 7. [Google Scholar] [CrossRef]
  77. Skomal, G.B.; Braun, C.D.; Chisholm, J.H.; Thorrold, S.R. Movements of the white shark Carcharodon carcharias in the North Atlantic Ocean. Mar. Ecol. Prog. Ser. 2017, 580, 1–6. [Google Scholar] [CrossRef]
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Figure 1. Location of the first detection location for SLRT and acoustic tags and class of SLRT detection for the 22 tagged White Sharks (Carcharodon carcharias) that were caught and released from SMART drumlines at Ballina, Evans Head, Coffs Harbour, and Tuncurry off eastern Australia.
Figure 1. Location of the first detection location for SLRT and acoustic tags and class of SLRT detection for the 22 tagged White Sharks (Carcharodon carcharias) that were caught and released from SMART drumlines at Ballina, Evans Head, Coffs Harbour, and Tuncurry off eastern Australia.
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Figure 2. Time until first detection (satellite-linked radio transmitters and acoustic tags) for White Sharks (Carcharodon carcharias) caught on SMART drumlines in the first (a) 50 h and (b) 250 h post-release.
Figure 2. Time until first detection (satellite-linked radio transmitters and acoustic tags) for White Sharks (Carcharodon carcharias) caught on SMART drumlines in the first (a) 50 h and (b) 250 h post-release.
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Figure 3. Box plot (median—dark line; upper and lower quartiles—box limits; maximum and minimum values—whiskers and outliers—circle) of the distance (km) from the coast for the 22 White Sharks (Carcharodon carcharias) that were detected within the first 10 days after capture and release from SMART drumlines.
Figure 3. Box plot (median—dark line; upper and lower quartiles—box limits; maximum and minimum values—whiskers and outliers—circle) of the distance (km) from the coast for the 22 White Sharks (Carcharodon carcharias) that were detected within the first 10 days after capture and release from SMART drumlines.
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Figure 4. Location of all detections (SLRT and acoustic tags) for each of the 22 White Sharks (Carcharodon carcharias) within the first 10 days after capture and release from SMART drumlines at four locations between the mid- and north-coasts of New South Wales (Tuncurry, Coffs Harbour, Evans Head, and Ballina).
Figure 4. Location of all detections (SLRT and acoustic tags) for each of the 22 White Sharks (Carcharodon carcharias) within the first 10 days after capture and release from SMART drumlines at four locations between the mid- and north-coasts of New South Wales (Tuncurry, Coffs Harbour, Evans Head, and Ballina).
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Figure 5. Explanatory models with 95% confidence intervals for distance (km) White Sharks (Carcharodon carcharias) were detected from the coast in relation to (a) time since release (hours), (b) total length (cm) of the sharks, and (c) shark sex.
Figure 5. Explanatory models with 95% confidence intervals for distance (km) White Sharks (Carcharodon carcharias) were detected from the coast in relation to (a) time since release (hours), (b) total length (cm) of the sharks, and (c) shark sex.
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Table 1. Capture (date and location), biological (sex and total length–cm), technical (accumulated time in minutes from hooking to release and being secured to the boat and release), secured, and movement details for time to first and last detection from SLRT and acoustic tags, and distance (km) from release location and the coastline for 36 White Sharks (Carcharodon carcharias) that were caught from SMART drumlines, tagged, and released.
Table 1. Capture (date and location), biological (sex and total length–cm), technical (accumulated time in minutes from hooking to release and being secured to the boat and release), secured, and movement details for time to first and last detection from SLRT and acoustic tags, and distance (km) from release location and the coastline for 36 White Sharks (Carcharodon carcharias) that were caught from SMART drumlines, tagged, and released.
Shark IDDateLocation ReleasedSexTotal Length
(cm)		Time from Hooking to ReleaseTime from Secured at the Boat to ReleaseDays to First Detection (All Classes)Days to First Detection in First 10 Days (Class 1–3)Distance (km) from Release
Location to First SLRT Detection (Class 1–3)		Distance (km) from Coast to First SLRT
Detection (Class 1–3)		Days to Last SLRT DetectionDays to First Acoustic
Detection on VR4G		Distance (km) from Release Location to First
Acoustic Detection
on VR4G		Days to Last Acoustic
Detection
Anywhere
1531 May 2016Main Beach, Evans HeadF23544290.19---2731234477
1631 May 2016Main Beach, Evans HeadM26559301.19---4801734573
1731 May 2016Main Beach, Evans HeadM24534200.66---460200404
182 June 2016Main Beach, Evans HeadF28058301.192.1889.012.218263474
254 July 2016South Ballina Beach, BallinaM29849202.447.5129.122.479122301073
264 July 2016South Ballina Beach, BallinaF26837190.62---109246545
275 July 2016South Ballina Beach, BallinaF36063231.131.1340.836.2508---
285 July 2016South Ballina Beach, BallinaM30647200.170.4015.214.79203509568
3021 July 2016Tuncurry Beach, TuncurryF22046250.160.247.87.6292786967
3121 July 2016Tuncurry Beach, TuncurryM26743320.100.218.67.885112751011
3322 July 2016Tuncurry Beach, TuncurryF29056260.800.8040.015.916517413108
3427 July 2016Crowdy Beach, Crowdy HeadF228523032.32---464454
351 August 2016Boambee Beach, Coffs HarbourM29364391.621.6224.16.1425428130804
361 August 2016Boambee Beach, Coffs HarbourF21448290.510.519.89.0546280140967
372 August 2016Boambee Beach, Coffs HarbourM26467304.09---19344140114
389 August 2016Sharpes Beach, BallinaF21557293.419.2478.58.5310280773
399 August 2016South Ballina Beach, BallinaF30563424.654.6521.46.044530171
409 August 2016Sharpes Beach, BallinaF25954290.830.8318.815.5871280860
4110 August 2016South Ballina Beach, BallinaF35050259.28---1061315860
426 September 2016Tuncurry Beach, TuncurryF22059380.850.9217.03.534451751075
447 September 2016Tuncurry Beach, TuncurryM21441244.204.2066.42.6168270220774
457 September 2016Tuncurry Beach, TuncurryM26254290.150.156.84.3388560399
478 September 2016Tuncurry Beach, TuncurryM197563016.36---2232339053
4827 September 2016Angels Beach, BallinaM29171495.285.2927.63.5758525786
4928 September 2016Lighthouse Beach, BallinaM17259305.455.4736.916.92626062961001
501 October 2016Sharpes Beach, BallinaM21363440.300.3614.313.823260311
512 October 2016Lighthouse Beach, BallinaM25651350.79---362235265676
522 October 2016Sharpes Beach, BallinaM3001214814.14---670--86
532 October 2016Sharpes Beach, BallinaM23271441.231.2353.518.0328113301411
544 October 2016Trestles Headland, BallinaF26778420.813.20107.910.9639---
554 October 2016Lighthouse Beach, BallinaF22337280.230.3015.314.1150---
566 October 2016Lighthouse Beach, BallinaM28160360.625.3525.524.218043230398
578 October 2016South Ballina Beach, BallinaF25063380.27---1825722961056
588 October 2016South Ballina Beach, BallinaF222542810.23---1472865486
598 October 2016Lighthouse Beach, BallinaF21348281.46---43---
6015 October 2016Lighthouse Beach, BallinaF3136545-----48230960
Table 2. GLMM: Model selection results, showing all models with an Akaike information criterion for small sample sizes (AICc) of less than 10. df = degrees of freedom, ΔAICc = delta AICc with the model with the lowest AICc shown as zero, the AICc weights, which can be interpreted as the conditional probability of that model, and TL = total length (cm).
Table 2. GLMM: Model selection results, showing all models with an Akaike information criterion for small sample sizes (AICc) of less than 10. df = degrees of freedom, ΔAICc = delta AICc with the model with the lowest AICc shown as zero, the AICc weights, which can be interpreted as the conditional probability of that model, and TL = total length (cm).
ModeldfΔAICcAICc Weight
Null30.000.35
Sex41.640.15
TL41.770.14
Time since tagged41.800.14
Sex + TL53.130.07
Sex + Time since tagged53.570.06
Time since tagged + TL53.610.06
Time since tagged + TL + sex65.150.03
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Butcher, P.A.; Lee, K.A.; Brand, C.P.; Gallen, C.R.; Green, M.; Smoothey, A.F.; Peddemors, V.M. Capture Response and Long-Term Fate of White Sharks (Carcharodon carcharias) after Release from SMART Drumlines. Biology 2023, 12, 1329. https://doi.org/10.3390/biology12101329

AMA Style

Butcher PA, Lee KA, Brand CP, Gallen CR, Green M, Smoothey AF, Peddemors VM. Capture Response and Long-Term Fate of White Sharks (Carcharodon carcharias) after Release from SMART Drumlines. Biology. 2023; 12(10):1329. https://doi.org/10.3390/biology12101329

Chicago/Turabian Style

Butcher, Paul A., Kate A. Lee, Craig P. Brand, Christopher R. Gallen, Marcel Green, Amy F. Smoothey, and Victor M. Peddemors. 2023. "Capture Response and Long-Term Fate of White Sharks (Carcharodon carcharias) after Release from SMART Drumlines" Biology 12, no. 10: 1329. https://doi.org/10.3390/biology12101329

APA Style

Butcher, P. A., Lee, K. A., Brand, C. P., Gallen, C. R., Green, M., Smoothey, A. F., & Peddemors, V. M. (2023). Capture Response and Long-Term Fate of White Sharks (Carcharodon carcharias) after Release from SMART Drumlines. Biology, 12(10), 1329. https://doi.org/10.3390/biology12101329

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