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17 pages, 2061 KiB

Open AccessArticle

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

by Paul A. Butcher, Kate A. Lee, Craig P. Brand, Christopher R. Gallen, Marcel Green, Amy F. Smoothey and Victor M. Peddemors

Biology 2023, 12(10), 1329; https://doi.org/10.3390/biology12101329 - 12 Oct 2023

Cited by 2 | Viewed by 2749

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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Figure 1

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. Full article ">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. Full article ">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. Full article ">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). Full article ">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. Full article ">

17 pages, 1294 KiB

Open AccessArticle

Bull Shark (Carcharhinus leucas) Occurrence along Beaches of South-Eastern Australia: Understanding Where, When and Why

by Amy F. Smoothey, Yuri Niella, Craig Brand, Victor M. Peddemors and Paul A. Butcher

Biology 2023, 12(9), 1189; https://doi.org/10.3390/biology12091189 - 31 Aug 2023

Cited by 4 | Viewed by 3427

Abstract

Unprovoked shark bites have increased over the last three decades, yet they are still relatively rare. Bull sharks are globally distributed throughout rivers, estuaries, nearshore areas and continental shelf waters, and are capable of making long distance movements between tropical and temperate regions. [...] Read more.

Unprovoked shark bites have increased over the last three decades, yet they are still relatively rare. Bull sharks are globally distributed throughout rivers, estuaries, nearshore areas and continental shelf waters, and are capable of making long distance movements between tropical and temperate regions. As this species is implicated in shark bites throughout their range, knowledge of the environmental drivers of bull shark movements are important for better predicting the likelihood of their occurrence at ocean beaches and potentially assist in reducing shark bites. Using the largest dataset of acoustically tagged bull sharks in the world, we examined the spatial ecology of 233 juvenile and large (including sub-adult and adult) bull sharks acoustically tagged and monitored over a 5.5-year period (2017–2023) using an array of real-time acoustic listening stations off 21 beaches along the coast of New South Wales, Australia. Bull sharks were detected more in coastal areas of northern NSW (<32° S) but they travelled southwards during the austral summer and autumn. Juveniles were not detected on shark listening stations until they reached 157 cm and stayed north of 31.98° S (Old Bar). Intra-specific diel patterns of occurrence were observed, with juveniles exhibiting higher nearshore presence between 20:00 and 03:00, whilst the presence of large sharks was greatest from midday through to 04:00. The results of generalised additive models revealed that large sharks were more often found when water temperatures were higher than 20 °C, after >45 mm of rain and when swell heights were between 1.8 and 2.8 m. Understanding the influence that environmental variables have on the occurrence of bull sharks in the coastal areas of NSW will facilitate better education and could drive shark smart behaviour amongst coastal water users. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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Figure 1
(A) Map of the coast of New South Wales (NSW) showing the locations of the 21 shark listening stations (points) and rivers (triangles) where juvenile bull sharks were tagged (rivers north to south: Richmond, n = 2, Clarence, n = 22, Bellinger, n = 5), and (B) total bull shark detections (bars) per biological group for each shark listening station from 2017 to 2023 and their respective distances to nearest river mouth (line). Full article ">Figure 2
Summary of total detections (n = 13,996) and tagged vs. detected bull sharks by shark listening station location, including numbers of (1) total bull shark detections (n = 4044, after hourly binning), (2) tagged bull sharks (n = 233) between 4 March 2009 and 14 December 2022 and (3) individual sharks (n = 111) detected by receiver locations between 13 July 2017 and 8 January 2023. Full article ">Figure 3
Male (left panel) and female (right panel) juvenile bull sharks (A–E) tagged inside the Clarence and Richmond Rivers and subsequently detected along the coast of New South Wales. Points represent respective shark sizes at tagging (Tag), and at first (Min) and last (Max) shark listening station detections. Histograms of detections by year, and as a function of distance from tagging locations, are included for each shark. Full article ">Figure 4
Group-specific spatio-temporal generalised additive models of (A) juvenile and (B) large bull shark occurrence along the coast of New South Wales as a function of the interacting effects between latitude degree and year (left panel) and binned hour of the day (right panel). The colour scales (left panel) represent the corresponding fitted model residuals. Horizontal dashed lines and shaded areas (right panel), respectively, represent the null effects and the 95% confidence intervals. Positive values on the vertical axis indicate an increased probability of occurrence, while negative values indicate an increased probability of absence (right panel). Full article ">Figure 5
Response curves of environmental generalised additive mixed models predicting the occurrence of large bull sharks along the coast of New South Wales, including the significant effects of (A) water temperature, (B) daily rainfall and (C) swell height. Horizontal dashed lines and shaded areas, respectively, represent the null effects and the 95% confidence intervals, respectively. Positive values on the vertical axis indicate an increased probability of occurrence, while negative values indicate an increased probability of absence. Full article ">

18 pages, 2433 KiB

Open AccessArticle

Spatial Dynamics and Fine-Scale Vertical Behaviour of Immature Eastern Australasian White Sharks (Carcharodon carcharias)

by Julia L. Y. Spaet, Paul A. Butcher, Andrea Manica and Chi Hin Lam

Biology 2022, 11(12), 1689; https://doi.org/10.3390/biology11121689 - 22 Nov 2022

Cited by 2 | Viewed by 3600

Abstract

Knowledge of the 3-dimensional space use of large marine predators is central to our understanding of ecosystem dynamics and for the development of management recommendations. Horizontal movements of white sharks, Carcharodon carcharias, in eastern Australian and New Zealand waters have been relatively [...] Read more.

Knowledge of the 3-dimensional space use of large marine predators is central to our understanding of ecosystem dynamics and for the development of management recommendations. Horizontal movements of white sharks, Carcharodon carcharias, in eastern Australian and New Zealand waters have been relatively well studied, yet vertical habitat use is less well understood. We dual-tagged 27 immature white sharks with Pop-Up Satellite Archival Transmitting (PSAT) and acoustic tags in New South Wales coastal shelf waters. In addition, 19 of these individuals were also fitted with Smart Position or Temperature Transmitting (SPOT) tags. PSATs of 12 sharks provided useable data; four tags were recovered, providing highly detailed archival data recorded at 3-s intervals. Horizontal movements ranged from southern Queensland to southern Tasmania and New Zealand. Sharks made extensive use of the water column (0–632 m) and experienced a broad range of temperatures (7.8–28.9 °C). Archival records revealed pronounced diel-patterns in distinct fine-scale oscillatory behaviour, with sharks occupying relatively constant depths during the day and exhibiting pronounced yo-yo diving behaviour (vertical zig-zag swimming through the water column) during the night. Our findings provide valuable new insights into the 3-dimensional space use of Eastern Australasian (EA) white sharks and contribute to the growing body on the general ecology of immature white sharks. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
Spatial scale of individual movements. Interpolated telemetry tracks of 12 juvenile white sharks tagged off eastern Australia from a combination of satellite-linked radio, pop-up satellite archival, acoustic and recapture records collected between 12 September 2017 and 1 March 2020. Positions are colour-coded by month. Arrows indicate tagging locations. Red square indicates the study area. ID numbers, sex and fork length of tagged sharks are indicated above each map. All maps were generated using the marmap package in R [<a href="#B37-biology-11-01689" class="html-bibr">37</a>]. Full article ">Figure 2
Depth and temperature occupation by latitudinal zones (north, central and south). Yellow dots represent positional data of all individual tracks (n = 12) displayed in <a href="#biology-11-01689-f001" class="html-fig">Figure 1</a>. (A,B) indicate percent time at depth and temperature by day (white bars) and night (grey bars) from Pop-Up Satellite Archival Transmitting tags (PSAT) data for each latitudinal zone. Error bars represent SDs. ‘IDs’ indicates the ID numbers of sharks for which depth and temperature records were included in each histogram. n1 and n2 indicate the number of depth and temperature records and the number of waypoints (points along estimated tracks) included in each histogram, respectively. Sharks for which depth or temperature data were missing for more than 25% of the total deployment days were excluded from the analyses. Red arrows indicate depth above which 95% of data occur for both day and night. Depth > 250 m were included into the 240–260 m bin. Temperatures < 12 °C were included into the 12–14 °C bin. For shark 180, all available depth and temperature data were included into the analysis, even though the full track of this shark is not shown in the zoomed-in map. The map was generated using the marmap package in R [<a href="#B37-biology-11-01689" class="html-bibr">37</a>]. Full article ">Figure 3
Vertical activity analysis based on recovered tag data. Coefficient of variation values and associated mean depth occupation for each of the four datasets displayed over 24 h for the entire tracking period for sharks 180, 356 and 365, 366. The same colour/numeric scale is shared by mean depth (in meters) and coefficient of variation in depth (expressed as a percentage). Dotted lines indicate times of local sunrise and sunset. Full article ">Figure 4
Fine–scale diving behaviour. Representative archival time-series depth and temperature data from shark 180 (210 cm FL, female). (A–C) Each plot on the left displays ten days of diving data collected at 3-s intervals and colour-coded by day. Areas shaded in grey indicate approximate night-time (darker grey) and twilight periods (lighter grey). (A–C) Plots on the right display the associated daily temperature records collected at 3-s intervals. Locations of track periods are indicated in the map. The map was generated using the marmap package in R [<a href="#B37-biology-11-01689" class="html-bibr">37</a>]. Full archival time-series depth and temperature data for all four recovered archival tags are available in the supplement (<a href="#app1-biology-11-01689" class="html-app">Figure S6</a>). Full article ">

16 pages, 1945 KiB

Open AccessArticle

Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia

by Jonathan D. Mitchell, Tracey B. Scott-Holland and Paul A. Butcher

Biology 2022, 11(11), 1552; https://doi.org/10.3390/biology11111552 - 23 Oct 2022

Cited by 1 | Viewed by 2270

Abstract

Drones enable the monitoring for sharks in real-time, enhancing the safety of ocean users with minimal impact on marine life. Yet, the effectiveness of drones for detecting sharks (especially potentially dangerous sharks; i.e., white shark, tiger shark, bull shark) has not yet been [...] Read more.

Drones enable the monitoring for sharks in real-time, enhancing the safety of ocean users with minimal impact on marine life. Yet, the effectiveness of drones for detecting sharks (especially potentially dangerous sharks; i.e., white shark, tiger shark, bull shark) has not yet been tested at Queensland beaches. To determine effectiveness, it is necessary to understand how environmental and operational factors affect the ability of drones to detect sharks. To assess this, we utilised data from the Queensland SharkSmart drone trial, which operated at five southeast Queensland beaches for 12 months in 2020–2021. The trial conducted 3369 flights, covering 1348 km and sighting 174 sharks (48 of which were >2 m in length). Of these, eight bull sharks and one white shark were detected, leading to four beach evacuations. The shark sighting rate was 3% when averaged across all beaches, with North Stradbroke Island (NSI) having the highest sighting rate (17.9%) and Coolum North the lowest (0%). Drone pilots were able to differentiate between key shark species, including white, bull and whaler sharks, and estimate total length of the sharks. Statistical analysis indicated that location, the sighting of other fauna, season and flight number (proxy for time of day) influenced the probability of sighting sharks. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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Figure 1
Map of Queensland SharkSmart Drone Trial beach locations in Southeast Queensland, Australia. Full article ">Figure 2
Schematic showing the position of drone transects relative to the flagged area of the beach. Full article ">Figure 3
Example images of sharks recorded during the Queensland SharkSmart drone trial. (a) white shark (Carcharodon carcharias), recorded at Southport Main Beach, Gold Coast in September 2020, (b) group of five large whaler sharks observed at Ocean Beach, North Stradbroke Island in November 2020, (c) whaler shark (Carcharhinus sp.) from the blacktip complex recorded at North Stradbroke Island in December 2020, (d) small whaler shark (Carcharhinus sp.) seen at North Stradbroke Island in January 2021, (e) bull shark (Carcharhinus leucas) recorded at Burleigh Beach in June 2021 and (f) whaler shark (Carcharhinus sp.) at North Stradbroke Island in December 2020. Full article ">Figure 4
Influence of significant predictor variables on the probability of sighting sharks, across all beaches where sharks were sighted. (a) location, (b) sighting of other fauna, (c) season, (d) flight number. Solid black lines indicate model fitted values. Grey shaded areas indicate 95% confidence intervals. Full article ">

16 pages, 2331 KiB

Open AccessArticle

SMART Drumlines Ineffective in Catching White Sharks in the High Energy Capes Region of Western Australia: Acoustic Detections Confirm That Sharks Are Not Always Amenable to Capture

by Stephen M. Taylor, Jason How, Michael J. Travers, Stephen J. Newman, Silas Mountford, Daniela Waltrick, Christopher E. Dowling, Ainslie Denham and Daniel J. Gaughan

Biology 2022, 11(10), 1537; https://doi.org/10.3390/biology11101537 - 20 Oct 2022

Cited by 1 | Viewed by 2109

Abstract

The management of human-shark interactions can benefit from the implementation of effective shark hazard mitigation measures. A Shark-Management-Alert-in-Real-Time (SMART) drumline trial in the Capes region of Western Australia was instigated after several serious incidents involving surfers and white sharks (Carcharodon carcharias). [...] Read more.

The management of human-shark interactions can benefit from the implementation of effective shark hazard mitigation measures. A Shark-Management-Alert-in-Real-Time (SMART) drumline trial in the Capes region of Western Australia was instigated after several serious incidents involving surfers and white sharks (Carcharodon carcharias). The project aimed to determine whether white sharks (target species), which were relocated after capture, remained offshore using satellite and acoustic tagging. Over a 27-month period, 352 fish were caught, 55% of which comprised tiger sharks (Galeocerdo cuvier). Ninety-one percent of animals were released alive in good condition. Only two white sharks were caught; both were relocated ≥ 1 km offshore before release and moved immediately further offshore after capture, remaining predominately in offshore waters for the duration of their 54-day and 186-day tag deployments. Our results confirm that desirable animal welfare outcomes can be achieved using SMART drumlines when response times are minimised. The low target catches and the detection of 24 other tagged white sharks within the study area supported the decision to cease the trial. Our results reiterate there is no simple remedy for dealing with the complexities of shark hazards and reinforce the importance of trialing mitigation measures under local conditions. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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Figure 1

Figure 1
Map of the Capes region of Western Australia highlighting the 10 fixed locations where SMART drumlines were deployed and the locations for the VR2 and VR4G or Rx LIVE receivers. Left panel displays the location of the drumlines in relation to popular surf breaks and the receivers within the Gracetown array. Right panel displays the primary and secondary receiver arrays and the location of the Capes region in relation to the state capital of Perth. Full article ">Figure 2
Relationship between the power of an experiment for varying sample size. This assumes a one-way test of one-sample proportion, with small, medium and large effect sizes specified by 0.2, 0.5 and 0.8, respectively, corresponding to an increase in proportion (from the base level with no mitigation) of approximately 0.09, 0.22 and 0.34 respectively. The effect size for two proportions are calculated using the arcsine transformation of the proportions. Numbers in colour denote the number of white sharks that would be required to be caught and relocated in order to detect an effect size. Full article ">Figure 3
Location of VR2 (open dots) and VR4 (open triangles) receivers off Gracetown with major surf breaks (black squares) and SMART drumline locations (filled triangles) indicated. Arrows are inferred straight-line movements for sharks between successive detection locations (solid dots). Relocation paths (dashed line) to release points and detections (solid dots) are presented for: (a) white shark 1; and (b) white shark 2. All acoustically tagged white sharks that were detected within the Gracetown array while SMART drumlines were being actively fished are presented in (c,d) with colours denoting separate movements through the array. Full article ">Figure 4
Estimated tracks of: (a) a 460 cm TL white shark caught on 25 April 2019, tag duration of 54 days; and (b) a 330 cm TL white shark caught on 20 August 2019, tag duration of 186 days. Tracks are based on model-estimated daily locations from PAT tags using GPE3. Full article ">Figure 4 Cont.
Estimated tracks of: (a) a 460 cm TL white shark caught on 25 April 2019, tag duration of 54 days; and (b) a 330 cm TL white shark caught on 20 August 2019, tag duration of 186 days. Tracks are based on model-estimated daily locations from PAT tags using GPE3. Full article ">

21 pages, 3207 KiB

Open AccessArticle

Quantifying Catch Rates, Shark Abundance and Depredation Rate at a Spearfishing Competition on the Great Barrier Reef, Australia

by Adam Smith, Al Songcuan, Jonathan Mitchell, Max Haste, Zachary Schmidt, Glenn Sands and Marcus Lincoln Smith

Biology 2022, 11(10), 1524; https://doi.org/10.3390/biology11101524 - 18 Oct 2022

Cited by 1 | Viewed by 2888

Abstract

We developed and applied a method to quantify spearfisher effort and catch, shark interactions and shark depredation in a boat-based recreational spearfishing competition in the Great Barrier Reef Marine Park in Queensland. Survey questions were designed to collect targeted quantitative data whilst minimising [...] Read more.

We developed and applied a method to quantify spearfisher effort and catch, shark interactions and shark depredation in a boat-based recreational spearfishing competition in the Great Barrier Reef Marine Park in Queensland. Survey questions were designed to collect targeted quantitative data whilst minimising the survey burden of spearfishers. We provide the first known scientific study of shark depredation during a recreational spearfishing competition and the first scientific study of shark depredation in the Great Barrier Reef region. During the two-day spearfishing competition, nine vessels with a total of 33 spearfishers reported a catch of 144 fish for 115 h of effort (1.25 fish per hour). A subset of the catch comprised nine eligible species under competition rules, of which 47 pelagic fish were weighed. The largest fish captured was a 34.4 kg Sailfish (Istiophorus platypterus). The most common species captured and weighed was Spanish Mackerel (Scomberomorus commerson). The total weight of eligible fish was 332 kg and the average weight of each fish was 7.1 kg. During the two-day event, spearfishers functioned as citizen scientists and counted 358 sharks (115 h effort), averaging 3.11 sharks per hour. Grey Reef Sharks (Carcharhinus amblyrhynchos) comprised 64% of sightings. Nine speared fish were fully depredated by sharks as spearfishers attempted to retrieve their catch, which equates to a depredation rate of 5.9%. The depredated fish included four pelagic fish and five reef fish. The shark species responsible were Grey Reef Shark (C. amblyrhynchos) (66%), Bull Shark (Carcharhinus leucas) (11%), Whitetip Reef Shark (Triaenodon obesus) (11%) and Great Hammerhead (Sphyrna mokarran) (11%). There were spatial differences in fish catch, shark sightings and rates of depredation. We developed a report card that compared average catch of fish, sightings of sharks per hour and depredation rate by survey area, which assists recreational fishers and marine park managers to assess spatio-temporal changes. The participating spearfishers can be regarded as experienced (average 18 days a year for average 13.4 years). Sixty percent of interviewees perceived that shark numbers have increased in the past 10 years, 33% indicated no change and 7% indicated shark numbers had decreased. Total fuel use of all vessels was 2819 L and was equivalent to 6.48 tons of greenhouse gas emissions for the competition. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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Figure 1
Extent of North Queensland Bluewater Invitational (NQBI) spearfishing competition and the survey location areas within the Great Barrier Reef Marine Park. The blue and yellow zones are waters where spearfishing is permitted and green zones are closed to spearfishing. Grid letters A–F and numbers 1–4 are used to label locations of NQBI competition. Full article ">Figure 2
Total effort (hours) of spearfishers between 27–28 November 2021. Grid letters A–F and numbers 1–4 are used to label locations of NQBI competition. Full article ">Figure 3
Differences in catch per unit effort (CPUE) ± SE of fish by day (top) and by location (bottom). See <a href="#biology-11-01524-f001" class="html-fig">Figure 1</a> for grid cell locations. Full article ">Figure 3 Cont.
Differences in catch per unit effort (CPUE) ± SE of fish by day (top) and by location (bottom). See <a href="#biology-11-01524-f001" class="html-fig">Figure 1</a> for grid cell locations. Full article ">Figure 4
Comparison of shark sightings (per hour) and shark species by survey location on 27–28 November 2021. Grid letters A–F and numbers 1–4 are used to label locations of NQBI competition. Full article ">Figure 5
Differences in shark sightings-per-unit-effort (SPUE) ± SE by day (top) and by location (bottom). See <a href="#biology-11-01524-f001" class="html-fig">Figure 1</a> for grid cell locations. Full article ">Figure 6
Non-metric multidimensional scaling (NMDS) comparing sightings-per-unit-effort (SPUE) of shark sightings (total assemblage) among locations (see <a href="#biology-11-01524-f001" class="html-fig">Figure 1</a> for grid cell locations). Full article ">Figure 7
Differences in depredation rates (% of catch) by day (left) and location (right). See <a href="#biology-11-01524-f001" class="html-fig">Figure 1</a> for grid cell locations. Full article ">Figure 8
Average catch of fish and sightings of sharks per hour by survey unit area and assessment of status of fish catch, shark numbers and depredation (see <a href="#biology-11-01524-t002" class="html-table">Table 2</a> for key). Grid letters A–F and numbers 1–4 are used to label locations of NQBI competition. Full article ">

16 pages, 2543 KiB

Open AccessArticle

The Relative Abundance and Occurrence of Sharks off Ocean Beaches of New South Wales, Australia

by Kim I. P. Monteforte, Paul A. Butcher, Stephen G. Morris and Brendan P. Kelaher

Biology 2022, 11(10), 1456; https://doi.org/10.3390/biology11101456 - 4 Oct 2022

Cited by 2 | Viewed by 2988

Abstract

There is still limited information about the diversity, distribution, and abundance of sharks in and around the surf zones of ocean beaches. We used long-term and large-scale drone surveying techniques to test hypotheses about the relative abundance and occurrence of sharks off ocean [...] Read more.

There is still limited information about the diversity, distribution, and abundance of sharks in and around the surf zones of ocean beaches. We used long-term and large-scale drone surveying techniques to test hypotheses about the relative abundance and occurrence of sharks off ocean beaches of New South Wales, Australia. We quantified sharks in 36,384 drone flights across 42 ocean beaches from 2017 to 2021. Overall, there were 347 chondrichthyans recorded, comprising 281 (81.0%) sharks, with observations occurring in <1% of flights. Whaler sharks (Carcharhinus spp.) had the highest number of observations (n = 158) recorded. There were 34 individuals observed for both white sharks (Carcharodon carcharias) and critically endangered greynurse sharks (Carcharias taurus). Bull sharks (Carcharhinus leucas), leopard sharks (Stegostoma tigrinum) and hammerhead species (Sphyrna spp.) recorded 29, eight and three individuals, respectively. Generalised additive models were used to identify environmental drivers for detection probability of white, bull, greynurse, and whaler sharks. Distances to the nearest estuary, headland, and island, as well as water temperature and wave height, were significant predictors of shark occurrence; however, this varied among species. Overall, we provide valuable information for evidence-based species-specific conservation and management strategies for coastal sharks. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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Figure 1
(a) Locations of beaches studied using drone surveying techniques along the coastline of New South Wales, Australia. Examples of shark species observed using drones ((b) a white shark (Carcharodon carcharias); (c) a greynurse shark (Carcharias taurus); and (d) a bull shark (Carcharhinus leucas)) during the study. Full article ">Figure 2
Detection rates for each beach location in relation to distance to the nearest estuary for (a) white shark, (b) bull shark, (c) greynurse shark, and (d) whaler shark species, and estimated response curves with a 95% confidence region. Points are sized proportionally to the total flight effort at each location proportional to the average effort. Thus, a weight of 1.0 equals average flight effort, <1 equals below average effort, and >1 equals above average effort. Full article ">Figure 3
Detection rates for each beach location in relation to distance to the nearest headland for (a) white shark, (b) bull shark, (c) greynurse shark, and (d) whaler shark species, and estimated response curves with a 95% confidence region. Points are sized proportionally to the total flight effort at each location proportional to the average effort. Thus, a weight of 1.0 equals average flight effort, <1 equals below average effort, and >1 equals above average effort. Full article ">Figure 4
Detection rates for each beach location in relation to distance to the nearest island for (a) white shark, (b) bull shark, (c) greynurse shark, and (d) whaler shark species, and estimated response curves with a 95% confidence region. Points are sized proportionally to the total flight effort at each location proportional to the average effort. Thus, a weight of 1.0 equals average flight effort, <1 equals below average effort, and >1 equals above average effort. Full article ">Figure 5
Detection rates for each beach location in relation to water temperature for (a) white shark, (b) bull shark, (c) greynurse shark, and (d) whaler shark species, and estimated response curves with a 95% confidence region. Points are sized proportionally to the total flight effort at each location proportional to the average effort. Thus, a weight of 1.0 equals average flight effort, <1 equals below average effort, and >1 equals above average effort. Full article ">Figure 6
Detection rates for each beach location in relation to wave height for (a) white shark, (b) bull shark, (c) greynurse shark, and (d) whaler shark species, and estimated response curves with a 95% confidence region. Points are sized proportionally to the total flight effort at each location proportional to the average effort. Thus, a weight of 1.0 equals average flight effort, <1 equals below average effort, and >1 equals above average effort. Full article ">

19 pages, 5852 KiB

Open AccessEditor’s ChoiceArticle

Preliminary Data about Habitat Use of Subadult and Adult White Sharks (Carcharodon carcharias) in Eastern Australian Waters

by Jessica L. Coxon, Paul A. Butcher, Julia L. Y. Spaet and Justin R. Rizzari

Biology 2022, 11(10), 1443; https://doi.org/10.3390/biology11101443 - 1 Oct 2022

Cited by 5 | Viewed by 3205 | Correction

Abstract

In eastern Australia, white sharks (Carcharodon carcharias) are targeted in shark control programs, yet the movement of subadults and adults of the eastern Australasian population is poorly understood. To investigate horizontal and vertical movement and habitat use in this region, MiniPAT [...] Read more.

In eastern Australia, white sharks (Carcharodon carcharias) are targeted in shark control programs, yet the movement of subadults and adults of the eastern Australasian population is poorly understood. To investigate horizontal and vertical movement and habitat use in this region, MiniPAT pop-up satellite archival tags were deployed on three larger white sharks (340–388 cm total length) between May 2021 and January 2022. All sharks moved away from the coast after release and displayed a preference for offshore habitats. The upper < 50 m of the water column and temperatures between 14–19 °C were favoured, with a diel pattern of vertical habitat use evident as deeper depths were occupied during the day and shallower depths at night. Horizontal movement consisted of north–south seasonality interspersed with periods of residency. Very little information is available for adult white sharks in eastern Australia and studies like this provide key baseline information for their life history. Importantly, the latitudinal range achieved by white sharks illuminate the necessity for multijurisdictional management to effectively mitigate human-shark interactions whilst supporting conservation efforts of the species. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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Figure 1
Location of tagging sites (red dots) on the northern New South Wales coast of eastern Australia. (a) Lennox Head, tagging site of white shark 1 (W1) and Ballina, tagging site of white shark 2 (W2), (b) Evans Heads, tagging site of white shark 3 (W3), and (c) W1 secured to the side of the vessel during tagging procedure (image provided by the New South Wales Department of Primary Industries). Map generated in QGIS. Full article ">Figure 2
(a) MiniPAT-348 Pop-up Satellite Archival Transmitting Tag and Domeier dart head used to anchor the MiniPAT tags and acoustic transmitters into the sharks musculature, and (b) dorsal fins of the three white sharks used in the present study. Images taken after completing tagging procedure, with MiniPAT tags, acoustic transmitters and conventional tags visible (images provided by the New South Wales Department of Primary Industries). Full article ">Figure 3
Track reconstruction of three white sharks (C. carcharias) tagged off the northern New South Wales coast of eastern Australia. Estimated track positions are colour-coded by month. Tagging locations indicated by white diamonds, and MiniPAT tag pop-up locations indicated by black diamonds. Maps were generated in R Statistical Software, version 4.1.0 [<a href="#B29-biology-11-01443" class="html-bibr">29</a>], using R packages ‘marmap’ and ‘ggplot2’ [<a href="#B32-biology-11-01443" class="html-bibr">32</a>,<a href="#B33-biology-11-01443" class="html-bibr">33</a>]. Full article ">Figure 4
Time spent (%±SE) at depth (m) during the day (white bars) and at night (grey bars) for three white sharks (C. carcharias) (a) W1, (b) W2 and (c) W3. Full article ">Figure 5
Time spent (%±SE) at temperature (°C) during the day (white bars) and night (grey bars) for one white shark (C. carcharias) individual (W2). Full article ">Figure 6
Mean depths (m) of three white sharks (C. carcharias) (a) W1, (b) W2 and (c) W3 plotted over a 24-h period (0–23 h AEST). White areas indicate daylight. Areas shaded in grey indicate night-time (darker grey) and twilight (lighter grey) periods. Full article ">Figure 7
Depth profiles of three white sharks (C. carcharias) (a) W1, (b) W2 and (c) W3 across the 120 d MiniPAT tag deployment. Full article ">

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2 pages, 954 KiB

Open AccessCorrection

Correction: Coxon et al. Preliminary Data about Habitat Use of Subadult and Adult White Sharks (Carcharodon carcharias) in Eastern Australian Waters. Biology 2022, 11, 1443

by Jessica L. Coxon, Paul A. Butcher, Julia L. Y. Spaet and Justin R. Rizzari

Biology 2022, 11(12), 1762; https://doi.org/10.3390/biology11121762 - 5 Dec 2022

Viewed by 1292

Abstract

In the original publication [...] Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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11 pages, 1784 KiB

Open AccessBrief Report

Shark Bite Reporting and The New York Times

by Christopher L. Pepin-Neff

Biology 2022, 11(10), 1438; https://doi.org/10.3390/biology11101438 - 30 Sep 2022

Cited by 1 | Viewed by 3731

Abstract

The social and political dynamics around human–shark interactions are a growing area of interest in marine social science. The question motivating this article asks to what extent media reporting by The New York Times has engaged beyond the lexicon of “shark attack” discourse [...] Read more.

The social and political dynamics around human–shark interactions are a growing area of interest in marine social science. The question motivating this article asks to what extent media reporting by The New York Times has engaged beyond the lexicon of “shark attack” discourse to describe human–shark interactions. It is important because different styles of reporting on human–shark interactions can influence the public’s perceptions about sharks and support for shark conservation. This media outlet is also a paper of record whose editorial style choices may influence the broader media landscape. I review reporting language from The New York Times for 10 years between 2012 and 2021 (n = 36). I present three findings: first, I argue that The New York Times has had an increased frequency in use of the term “shark bite” to describe human–shark interactions. Secondly, I find that shark “attack” is still used consistently with other narratives. Third, there appears to be an increased use of “sightings; encounter; and incident” descriptors since 2020. The implication of this is a layered approach to reporting on human–shark interactions that diversifies away from a one-dimensional shark “attack” discourse. Full article

(This article belongs to the Special Issue Understanding and Managing Human–Shark Interactions in an Environmentally Aware World)

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