1. Introduction
Whales have started to recover from commercial whaling in the past century, resulting in positive population trends for some species such as humpback whales (Megaptera novaeangliae). However, increasing anthropogenic impacts from pollution, boating, fishing, climate change, and offshore development have caused an increase in whale mortality and, consequently, strandings [1,2,3]. On the east coast of the USA, 37 humpback whale strandings were reported in 2023 (NOAA,
While the majority of deceased whales never reach the shoreline, those that do can become a hazard. The removal of deceased whales that wash up or float near populated coastal areas can be a logistical challenge and receives attention from the public. In some instances, costly exhumation of beached, buried whales was required after public concerns were expressed that a carcass might attract sharks to the area (ABC News,
Complexity arises from the considerable size of the deceased whales, the diverse potential locations for strandings or floating whales, and challenges associated with accessing certain beaches. There are also technical, social, economic, and environmental factors to consider [6].
There are currently seven different disposal strategies recognized as possible management responses regarding deceased whales (Appendix A Table A1). In populated areas, whale remains may be transported to landfill (1). This requires adequate transportation and use of an excavator. It is most feasible when beaches are accessible and have a landfill or holding facility in proximity. The disposal of whale remains in landfills can be culturally controversial and raises ethical questions. There are also concerns due to the potential for disease transmission during handling. Decomposition of organic matter in landfills produces gases such as methane and carbon dioxide. In some cases, the deceased whale may be transported to a rendering facility (2), where it is processed and turned into products such as biodiesel. Composting is another option, wherein the deceased whale is placed in a controlled environment to decompose naturally, and the resulting compost can be used as fertilizer [7]. The burial of deceased whales (3) on or near the beach is frequently employed as a management strategy, particularly with smaller whale species. This involves digging a trench and burying the carcass in the sand. While burying whale carcasses can contribute to nutrient cycling and enhance coastal ecosystems, influencing soil composition and fostering local flora, it also presents challenges. This includes the potential spread of diseases, groundwater contamination, and the attraction of scavengers, which may impact local fauna and give rise to public health concerns [8,9].
Allowing natural decomposition (4) to occur is a strategy often employed in remote locations or with smaller whale species. Over time, the carcass breaks down through biological processes and the remains are dispersed by ocean currents. This method is not feasible on frequently visited public beaches due to unpleasant smell, sight, and associated health risks.
In cases where the carcass is large and close to shore or partially stranded, one strategy is to tow it (5) out to deeper waters. By releasing the carcass away from the coastline, it allows natural processes, such as decomposition and scavenging by marine organisms, to occur without affecting coastal ecosystems. This strategy can be regarded as the most ethical and culturally sensitive form of dealing with deceased whales. However, there are challenges associated with offshore disposal, such as the need for the whale to be repositioned in offshore regions that represent the least possibility for a return to shore, while also not posing a navigational hazard. Furthermore, repositioning deceased whales offshore also requires expertise, suitable weather conditions, and appropriate vessels and crew for towing and release operations.
In some instances, attempts have been made to sink deceased whales (6) to the ocean floor. This can be achieved by attaching weights or other materials to a floating carcass or a whale towed offshore. The idea is to reduce the risk of whale remains floating ashore as well as reducing any navigational hazards. This method has been deployed in the past to study decomposition rates of whale carcasses in various oceans [10]. Explosives (7) have been used historically to break down large deceased whales into smaller, more manageable pieces [6]. This method is less common today due to obvious safety and environmental concerns. Generally, the scientific community recognizes that the disposal of whales demands careful planning and execution to mitigate potential adverse effects. Whether offshore disposal is suitable depends on a number of factors, including external factors such as weather conditions, size of whale, and the type and number of scavengers influencing decomposition rates.
1.1. Large Whale Offshore Disposal and Decomposition
Following death, baleen whales (Mysteceti) can significantly expand, causing them to float until forces of wind and waves, degradation from sunlight, and damage from scavengers reduces buoyancy (Figure 1). If there is sufficient buoyancy retained in fatty tissues, whale remains may linger at, or close, to the water’s surface while denser tissues, like bones, are shed. Different whale species also have different density and buoyancy characteristics. For instance, Right whales (Eubalaena glacialis, E. australia) are more buoyant on the surface than humpback whales (Megaptera novaeangliae) [11]. During a mortality event with 14 humpback whales over a 5-week period in 1987 at Cape Cod Bay, USA, all whales (except one that was towed immediately after death) sank then re-floated due to gas produced during decomposition [5,12].
Water temperature plays a key role in gas production from gut bacteria. It can be estimated that it takes about 24 h at 30 °C and 3–5 days at 20 °C for a baleen whale to refloat (pers. communication). Warmer sea temperatures will enhance bacterial growth resulting in faster heat development inside the deceased whale body [13]. A sperm whale (Physeter macrocephalus) (10 m) in the Seychelles, which presented a water temperature of 29 °C, was floating at first sight and then anchored with 5–6 tiger (Galeocerdo cuvier) and bull sharks (Carcharhinus leucas) feeding at any one time. After 5 days, the whale remains were consumed and sank [14]. Scavengers such as tiger sharks play a crucial role in reducing the time a deceased whale stays afloat (Video S1). Tiger sharks actively target the blubber and avoid muscle tissue [10,15], thereby reducing the buoyancy of a deceased whale. Further reports and studies from large deceased whales (10 m and more) from South Africa (water temperature of 14 °C) suggest a longer decomposition time at the surface (>7 days), even in the presence of sharks [16]. The duration of sharks lingering at the site where whale remains occurred or are buried was observed to be 7 days, with duration of stay decreasing daily due to a reduction in scavenging success [17].
1.2. Modelling Drift
Whale remains have been towed out to sea for offshore disposal in a number of countries, including Australia, South Africa, and the USA [6]. However, not all of these offshore disposals were successful. For example, a humpback whale washed ashore again after being towed out to sea near Los Angeles, USA, underlining the importance of estimating drift and the best disposal locations (The Guardian,
Predictions regarding the movement of deceased whales adrift at sea can be useful in supporting the comprehension of likely stranding sites along coastlines, in concert with an understanding of the potential for the presence of whale remains in shipping lanes or coastal waters frequented by the public for activities such as swimming, fishing, and other recreational activities. Safety considerations for coastal water community users should encompass the potential for the deceased whale to draw predatory sharks, in addition to posing a hazard to boating.
Drift of whale remains, or any objects, is predominantly influenced by wind and current forcing. Buoyancy influences the drift speed, with whale remains being more driven by wind the more buoyant they are and the more inflated they are above the water surface. There are several models that allow for object drift tracking at sea that consider factors such as wind and currents. A study on deceased floating common dolphins (Delphinus delphis) near the French Atlantic coast was performed using the drift prediction model MOTHY (Modèle Océanique de Transport d’HYdrocarbures). Originally devised by Météo-France for forecasting the movement of oil slicks, MOTHY was subsequently modified to accommodate solid objects such as cargo containers [18]. The MOTHY model forecasts the trajectories of floating objects by computing the vertical profile of currents and assessing the impact of wind on the exposed portion of the object [19]. Hydrodynamic models such as the America SEAS (AMSEAS) model were applied to deceased floating turtles in the Gulf of Mexico [20]. Another software package is the Search and Rescue Model and Planning (SARMAP) model that is capable of predicting the movement of various floating objects (e.g., person in the water, rafts or capsized boats on the sea surface) in compressed time mode for search and rescue missions [21]. To achieve this, SARMAP uses inputs such as spatially and time-varying winds and currents, along with the drift characteristics specific to the floating object.
Here, we investigate and validate the projected drift trajectories of a deceased whale at sea that required consideration of various factors such as environmental conditions, ocean currents, and the size of the carcass to enhance our understanding of its movement patterns. We further discuss the implications of the case study’s findings for the potential improvement of offshore disposal practices and their relevance in comparison to other existing management strategies for stranded whale carcasses.
2. Materials and Methods
The study area is located in the waters of the Sunshine and Fraser Coast in southeast Queensland, Australia (Figure 2). Specifically, the location is between Noosa Headlands in the south (26.378° S, 153.119° E) and Double Island Point in the north (28.168° S, 153.558° E) and further north to Fraser Island (25.793° S, 153.077° E), with a mean water depth ranging from 10 m nearshore to 60 m approximately 30 km offshore. The region is part of the fast-growing south-east Queensland region [22]. The coastal area is dominated by sandy beaches and an open embayment facing towards the Coral Sea. Regional climate conditions are characterized by a sub-tropical hot and humid wet season (November–April) and a mild dry season (May–October) with mostly easterly to south-easterly trade winds all year. The sea surface temperature (SST) ranges from 20 °C to 28 °C between the wet and dry seasons, respectively [23]. The East Australian Current (EAC) brings warm, tropical water from the north and a coastal, northward current generally brings cooler waters. The strength of these currents varies with the seasons, with the EAC weakening during the Austral winter months between May to November [24]. During the autumn and winter months, the wind-driven Fraser Island Gyre develops between southern Fraser Island (25° S) and Moreton Bay (27° S), creating a near-coast northern flow and cross-shelf transport [25]. Mean significant wave height of the region is around 1 m [26], and there is a predominance of south-easterly waves. A semidiurnal tide with a 1–2 m range creates tidal flows nearshore.
2.1. Whale Remains and Position Tracking
In the afternoon (4:00 p.m.) of the 16 July 2023, a floating whale was reported by Australian Volunteers Coastguard south of Noosa Heads (Figure 2; 26.481° S, 153.334° E) with a northwest drift. It was then resighted approximately 4 km northwest from Noosa Heads the next day. The whale remains were identified as a female humpback whale with an estimated size of 14 m total length, an approximate body width of 5 m, pectoral fins each 4–5 m in length, and a total weight between 20–25 t. The height of the animal exposed above the water surface was estimated at 1.5 m. As the head of the whale was missing, it is assumed the whale was likely killed by a ship strike in previous days. Decomposition of the whale had begun, with multiple shark bite marks visible and an inflated body indicating gas development from the intestines (Figure 3).
A fully charged DAF SPOT Trace satellite tag (
2.2. Drift Trajectory Modelling
The SARMAP (RPS, Version 7.1.1.11) drift modelling software, developed by Applied Science Associates, Inc. [27], was employed in this study to forecast the drift of the whale remains. SARMAP has undergone validation through numerous global studies [28,29,30,31]. SARMAP operates as a Lagrangian particle tracking model, designed to predict the movement of various floating objects on the sea surface [32,33]. In this study, SARMAP utilized the Monte Carlo method to compute the drift of the carcass, whereby 1000 particles were released to forecast the movement of the modelled whale remains. The model calculates the spatial and temporal variations of each particle based on the drift or leeway characteristics of the selected object and metocean conditions. The results derived from the simulation are presented as a time-varying spatial density map, offering insights into the potential drift path of the target over time.
2.3. Search Object Database
The combined effect upon the drift of an object due to wind and waves is described as the “leeway”. The leeway of an object varies from object to object and therefore a set of measured leeway coefficients is specified for each drift object to accurately determine their drift characteristics. Without the correct leeway coefficients, it is impossible to accurately forecast how that object may drift. Leeway field tests are currently the most common and most accurate method for determining the leeway coefficients of a drift object [33,34]. This process entails measuring how an object drifts in response to surface currents, influenced by wind and wave action. The latest definition, proposed by Breivik et al. [35], describes leeway as the motion induced by wind (at 10 m reference height) and waves relative to the ambient current (between 0.3 and 1.0 m depth).
In SARMAP, users have access to a database containing drift behavior for 101 objects, which is based on established U.S. Coast Guard datasets. This database enables users to select the most suitable object for their situation. However, no leeway data were available, at the time of this study, for whale remains, and the influence of the winds blowing against the exposed surfaces of the whale is not well understood. An assessment of the SARMAP object database was undertaken to select objects that could potentially best represent a deceased floating whale. As such, individual modelling simulations were initially conducted using both a (i) life raft equipped with a deep ballast system and canopy with a windage of 0.9% and a (ii) skiff in a swamped or capsized condition with a windage of 1.7%, in order to gauge the different drift behavior.
2.4. Environmental Data
In SARMAP, the simulated drift of an object is divided into two primary velocity components. The first velocity component represents the drift of the object caused by the mean flow field, typically obtained from current and wind forecast models. The second velocity component accounts for the drift due to turbulence also known as horizontal dispersion, which encompasses sub-grid scale processes that may not be accurately replicated in current and wind models. By treating these two velocity components separately, SARMAP can effectively account for the contributions from both large-scale circulation and smaller-scale turbulent motion, enabling a more comprehensive understanding of the object’s drift behavior.
The currents within the study area are influenced by tidal flows and large-scale drift currents, which are driven by factors such as wind shear on the water surface and the presence of the EAC, which impinges close to the coast. To accurately characterize the “total current”, the influence of tidal and ocean current data was included as input into SARMAP.
Tidal current data were generated using RPS’ advanced ocean/coastal model, HYDROMAP. This model simulates tides resulting from astronomical tides, wind stress, and bottom friction [36]. Employing a sophisticated dynamically nested-gridding strategy, the tidal model domain for this study was sub-gridded to a maximum resolution of 500 m along the coastline, starting from an offshore resolution of 8 km.
Data from three global ocean current models were sourced for individual comparison as part of the consensus forecasting approach (Table 1). These models included BLUElink, Hybrid Coordinate Ocean Model (HYCOM), and Copernicus Global Operational Forecast (Copernicus). There was consensus among the three ocean current models, although the Copernicus model product (Copernicus,
Given that the atmospheric fields driving the Copernicus ocean model originate from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System, we utilized the same wind data to incorporate wind forcing affecting the carcass. A more detailed presentation of the model can be found in Lellouche et al. [37].
2.5. Dispersion Parameters
The horizontal dispersion coefficient serves two primary purposes within drift models: (i) compensating for drift associated with sub-grid scale turbulent processes not accounted for by ocean forecast models and (ii) addressing uncertainties within environmental forcing data, including waves, winds, and currents. The values of horizontal dispersion vary across regions and over time, depending on the amount of horizontal current shear or turbulence present. Using too large a value can cause particles to separate, leading to a larger predicted area; while this increases the likelihood of containing the object, it compromises the accuracy of predicting whether the whale remain would strand on a public access (recreational) beach. During this study, sensitivity testing was conducted using varying literature-based horizontal diffusion parameters for nearshore coastal and ocean waters, ranging from 5 m2/s and 10 m2/s.
2.6. Comparison of Simulated Trajectory and Satellite Track
For a measure of the quality of fit, we used the average track error calculated as the mean distance between hourly model predictions and corresponding positions of the tracked whale remains based on time. Additionally, the hourly measured drift speed and direction of the whale remains were compared with modeled hourly wind speeds and directions to assess the drift characteristics over time.
Pearson correlations were used to explore data and identify relationships between whale remains drift speed with wind speed. A criterion of p < 0.01 was used to determine significant differences using SPSS for Windows (SPSS Inc., Chicago, IL, USA, version 20). No data transformations were performed.
3. Results
During the observation period, the sea surface water temperature was 21 °C, the maximum wave height was 4 m, and the average wave height 1.5 m (based on local wave rider buoys from Wide Bay and Mooloolaba, Figure A1). The main wind direction until the 19 July 2023, was southeast to south with a maximum wind speed at sea of approximately 30 km/h. The wind direction changed to northeast for several days and then, on the 22 July 2023, to southeast with 40–50 km/h. These highly variable wind directions and wind speeds influenced the drift of the whale remains.
The observation period of the whale remains spanned 16 July 4:00 p.m. until 25 July 3:00 a.m. (179 h), of which 150 h were covered with a satellite tracker with 5 min interval location recordings (data telemetered). When first sighted, the deceased whale drifted 26.2 km within 22 h towards the Sunshine Coast with an average speed of 1.2 km/h. Thereafter the deceased whale was resighted the next day at approximately 12:00 p.m. and had drifted another 17.5 km at 1.1 km/h before it was relocated offshore on the 18 July 2023 from where it drifted at an average speed of 0.7 km/h for over 171 km until the satellite tag signal was lost. A gradual decline of drift speed and the effect of wind on drift speed (Table 2), even under increased wind speed conditions, was apparent (Figure A2). The drift of the deceased whale significantly correlated with wind speed, in particular within the first days of observation between 18th and 20th July, 2023 (r2 = 0.38, p < 0.01), though the correlation between whale remains drift speed with wind speed declined between 21 and 25 July 2023 (r2 = 0.24, p < 0.01) (Figure 4 and Figure A3a,b). The drift speed and modelled wind direction was more correlated in the first days and modelled current speed became more correlated to the drift speed of the whale remains in the last days of observation.
Due to the sequence in the availability of data, we initially simulated the drift of the deceased whale for the 18–25 July 2023 (Figure 5a) and then 16–18 July 2023 (Figure 5b).
The initial forecast modelling involved simulating the drift of the deceased whale immediately following the time after it was taken offshore and released on 18 July 2023, at approximately 2:00 p.m. The coordinates, date/time, and description of the whale state (Figure 3), which suggested advanced decomposition with parts of the whale body missing, were available. Inputs into the SARMAP model included ocean current data (plus HYDROMAP tides) and ECMWF winds. Upon assessment of the ocean current data, it was found that the deceased whale was released in a transition zone between coastal northward currents and the offshore southward EAC. Due to the advanced decomposition of the whale and the unknown influence of the winds, we selected two objects within SARMAP (a life raft and a skiff) with different windage factors to assess their drift behavior. The skiff, having double the windage, travelled further north than the life raft. The drift of each object type was very similar across all three ocean current models. Once the corresponding positions of the tracked whale remains were available, it was found that the drift of the skiff matched most accurately, while the model predicted life raft drift was too slow. This trend was consistent across all three ocean current products, with the Copernicus global ocean data (plus HYDROMAP tides) and ECMWF winds providing the best simulation output, matching the same distance and direction as the tracked deceased whale between the 18–25 July 2023.
Subsequently, the effect of the swamped skiff potential drift based on horizontal dispersion coefficient values of 5 m2/s and 10 m2/s was assessed. While the larger value of 10 m2/s increased the likelihood of containing the drifting deceased whale, we opted to use 5 m2/s as the results were similar (Figure 6) and reduced the likelihood of overstating that the whale remains would wash ashore.
Next, modelling of the deceased whale for the 16–18 July 2023, was initially based on the same settings as the first simulation: a swamped skiff, Copernicus global ocean data (plus HYDROMAP tides), ECMWF winds, and a 5 m2/s horizontal dispersion coefficient. Upon comparison with the actual track, the swamped skiff was found to be too slow, covering only one-third of the distance travelled by the deceased whale over the two days. As previously mentioned, the deceased whale was determined to have travelled at an average speed of at least 1.1 km/h, which interestingly was faster than was observed between 18–25 July 2023 (average speed of 0.7 km/h for over 170 km until the signal was lost), suggesting either less drag below the water surface or the whale sitting higher above the water surface. To address this, an alternative object from the SARMAP database was sought, one that would be influenced by the wind three times as much as a swamped skiff. As such, a Panga skiff POB (person on-board) 5 was selected and given a windage of 4.8%, representing 2.8 times greater wind influence compared to the swamped skiff (i.e., 4.8% compared to 1.7%). The Panga skiff’s POB 5 drift from the initial observation point on 16 July provided the better simulation of the whale track until 2:00 p.m. on 17 July 2023, compared to the swamped skiff. It then followed a similar path as the whale remains for the next 17 h, concluding within the vicinity of the location as indicated by the GPS tracker at 7:00 a.m. on 18 July 2023 (Figure 5b).
4. Discussion
In this study, we established a better understanding of the predictability of the drift speed and direction of whale remains. Using the drift model SARMAP and testing various input parameters effectively simulated the whale remains trajectory matching the SPOT tagged whale remains track. Covering more than one week of observation, the whale remains were exposed to a wide range of environmental factors. The highly variable weather and wind conditions as well as different currents and progressing decomposition provided for a unique opportunity to study the drift and test forecasting abilities. The reliable prediction of the drift of whale remains has major implications for their offshore disposal, navigation, and beach safety.
4.1. Offshore Whale Carcass Disposal Enhanced through Modelling Drift
Our case study showed that providing a reliable prediction of the drift of whale remains is achievable. Such capability would allow authorities to act when intervention is necessary. Forecasts for the drift of whale remains may be used to understand potential stranding locations along the coast as well as the potential for interaction with shipping lanes or coastal waters used by the public for swimming, fishing, and other recreation activities [38]. Safety considerations might also include the potential for the remains to attract sharks.
Additionally, it may be beneficial for forecasting the cost-effectiveness of towing whale remains to various offshore distances or directing the tow to specific locations where ocean currents and wind patterns favor keeping the remains at a safe distance from shore and/or high-density vessel use regions.
The drift of whale remains results from the dynamic interaction of wind, waves, and current forces. This balance shifts depending on the surface areas of the whale’s body exposed to wind and surface water. Variable buoyancy also plays a crucial role. A bloated deceased whale, which has increased windage, will be more affected by wind, whereas a low-lying carcass with minimal wind exposure will be more influenced by surface currents. Information about the condition of the deceased whale, including size, predation effects, loss of pectoral fins, decomposition stages, and height above the water line, is essential for accurately setting drift model parameters. Some of this information was available from photos such as the estimated height above water; however, the gradual rate of decomposition was unknown. The role of predators on the decomposition rate and therefore drift behavior can not be underestimated as our case study demonstrated [15,16].
Initially, the deceased whale was predominantly driven by wind speed, but, with continuing decomposition, this changed, resulting in a decrease in drift speed (Table 2). When modelling the drift for the first two days, simulating the drift with an object that had higher windage (Panga) was more accurate than one with lower windage (skiff). After 3 days, however, an object such as a skiff with less windage predicted the drift trajectory better (Figure 5). The deceased whale was determined to have drifted at an average speed of at least 1.1 km/h. This suggests either less drag below the water surface or the whale sitting higher above the water surface between 16th and 18th July, resulting in faster drift due to wind influence. This estimate of the whale remains drift fitted well within the overall range for other drifting objects. For example, a variety of objects windage reviewed in Breivik et al. (2011) included persons in a survival suit (2% windage); life rafts (3–6.8% windage); fishing vessels (2.7–4.2% windage); and sport boats (6–7% windage). A horizontal dispersion coefficient of 5 m2/s instead of 10 m2/s was leading to a smaller predicted area and reduced the likelihood of the whale remains becoming stranded on a public access (recreational) beach.
Based on available knowledge, we estimated the total time from death until whale fall to be between 7–10 days in subtropical waters at water temperatures around 20–21 °C with sun exposure as well as presence of scavengers [15,39]. The whale remains were first sighted on the 16th July when the whale was likely already deceased for 2 days. The signal from the GPS tracker was lost in the early morning of the 25 July, which would be in line with the estimated 10 days for a whale fall to occur. This includes an estimated 2 days for the whale to refloat shortly after it deceased [5]. The majority of whales first sink after death but resurface after a few days unless they sink below 100 m hydrostatic pressure [40]. A humpback whale in subtropical Algoa Bay, South Africa, of 13 m length was observed for 12 days [39] until it finally sank. Another example from subtropical waters was a deceased humpback whale drifting near Marin County in California, USA. The carcass was estimated to have been adrift for no more than 2 or 3 days and was observed for another 7 days [15]. Higher temperatures accelerate the rate of oil leakage, which reduces buoyancy. Elevated air temperatures and extended exposure to sunlight cause internal heat to rise to nearly 50 °C within two to three days. This heat, coupled with autolysis, breaks down the fatty acids in the blubber [13]. Examples of floating deceased whales from tropical waters underline these observations. In New Caledonia a blue whale (Balaenoptera musculus) of 17.4 m length first sank after it died and resurfaced bloated after 36 hrs and sank permanently after 2 days but was subject to intensive feeding by over 40 tiger sharks, exposed to sun and warm waters [10].
This suggests that scavengers can play a major role in the decomposition in combination with warm waters (>24 °C) [41] as they are targeting blubber and meat, which accounts for over 60% of the whale body mass. An adult humpback whale consists, by weight, of ~23% blubber, ~40% meat, ~15% bone, and ~15% viscera (internal organs) [42].
4.2. Study Limitations
Many factors influence an object’s drift, including the speed and direction of winds and currents (large scale and tidal) and the object’s dimensions including height above water surface; however, these factors also have varying effects over time with the decomposition of the whale remains. We were unable to verify the status of the whale remains after the 18 July due to weather conditions and inaccessibility of area. The GPS tracker signal was lost for 11 h, which may be due to the whale body tipping and the tracker being submerged. Given the limited knowledge on decomposition rates in different environmental conditions for floating deceased whales, the time of whale fall could also not be verified. The larger the object’s surface area above the water level, the greater the influence of wind. For example, the divergence angle for a vessel is more than 45 degrees to the right and left of the average drift line. Ensuring improved reliability of forecasting the drift of whale remains requires additional observations for validation from different drifting whale remains from other locations.
To date, while models such as SARMAP are capable of simulating the drift trajectory of floating whale carcasses, they are unable to account for changes in decomposition, and global ocean models have limitations in nearshore waters [43]. This results in higher uncertainty in the prediction of the whale remains drift. In our case study, this uncertainty was in the range of 15–20 km (Figure 5). Other modelling techniques such as MOTHY, integrating hydrodynamic modelling with floating objects simulation and generally improving hydrodynamic models, could further advance the forecasting abilities. The America SEAS (AMSEAS) hydrodynamic model provides an estimate of leeway and then successfully applied modelling to the drift of deceased turtles [20]. Predictions of ocean currents are less reliable in nearshore coastal waters where the resolution of data is not sufficiently resolved. In shallow environments, drag or periods of short-term stranding on the seabed will also affect the movement of the carcass. Estimates of the draft (depth penetration) of the carcass will allow reference to the bathymetry in the area.
5. Conclusions
Offshore disposal of deceased whales requires careful consideration of various factors such as the size of the whale, its state of decomposition, proximity to human activities, and prevailing weather and sea conditions. Balancing the ecological benefits with potential risks is essential, and employing evidence-based approaches ensures responsible and sustainable management practices.
Perished whales provide a substantial nutrient source for marine ecosystems. Strategically placing whale carcasses offshore can enhance nutrient cycling and foster biodiversity contribute to carbon removal and marine floor enrichment [44] and enrich the marine floor for up to seven years [45]. Their gradual decomposition sustains scavengers and detritivores while also supporting microbial communities and deep-sea organisms. This underscores the ecological significance of offshore whale carcass disposal, advocating for sustainable practices that harmonize with natural ocean processes.
The best strategy for handling whale remains depends on multiple factors and must be decided on a case-by-case basis. Offshore disposal can be an ethical, cost-effective, and safe option if managed appropriately. Predictability of the drift of whale remains is an effective way to minimize risks. By integrating scientific research with practical management strategies as well as fostering collaborations between coast guard organizations and scientists, we can enhance our ability to predict and effectively manage the drift of whale carcasses, ensuring that ecological benefits are maximized while minimizing any adverse impacts.
Conceptualization, J.-O.M.; methodology, S.Z., L.P., R.J.K.D., N.B. and J.G.; validation, J.-O.M.; formal analysis, S.Z., L.P., R.J.K.D., N.B. and J.G.; resources, J.-O.M. and S.B.; writing—original draft preparation, J.-O.M.; writing—review and editing, J.-O.M., S.Z., L.P., R.J.K.D. and N.B.; visualization, J.-O.M., S.Z., L.P. and R.J.K.D. All authors have read and agreed to the published version of the manuscript.
Research was undertaken under Queensland Permit WA0051904 and Commonwealth water permit CP2021.0002.
Not applicable.
Data is available on request.
The authors like to thank Paddy Marine for providing expertise and assistance in the field. Photographs and videos used with permission from Paddy Marine, Laura Gourgas, and Queensland Department of Environment and Science.
Author Jan-Olaf Meynecke was a board member of the company Humpbacks & Highrises Inc. Authors Sasha Zigic, Larissa Perez, Ryan J. K. Dunn and Nathan Benfer were employed by the company RPS Ocean Science and Technology. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Enlarge this image.Figure 1. Illustration of removal of deceased whales offshore and relevant factors influencing the drift of floating whale remains. Sun exposure, water temperature, and scavengers contribute to decomposition rates with wind, waves, tides, and currents, as well as rate of decomposition, determining the drift.
Enlarge this image.Figure 2. Study location and track of whale remains. First sighted on the 16 July 2023 at 4:00 p.m. (A), resighted on the 17 July 2023 at 1:26 p.m. and a satellite tracker deployed (B), intercepted on the 18 July 2023 at 7:00 a.m. and towed offshore (C), released with satellite tracker at 1.40 p.m. (D) and last signal from satellite tracker received on the 25 July 2023 at 3:00 a.m. (E).
Enlarge this image.Figure 3. (a) Inflated deceased whale and tiger sharks (Galeocerdo cuvier) sighted on 17 July 2023, (b) clearly visible bite marks from tiger sharks, (c) side view of deceased whale with deployed satellite tracker on the 17 July 2023, (d) deceased whale with redeployed satellite tracker on the 18 July, 2023 (Images credit Paddy Marine).
Enlarge this image.Figure 4. Hourly drift of the deceased whale (dashed line) for available observation times in relation to hourly modelled wind speed (grey line).
Enlarge this image.Figure 5. (a) Predicted track of the whale remains from the observation point 18–25 July 2023, based on a life raft and a swamped skiff and (b) predicted track of the whale remains from the observation point 16–18 July 2023, based on a simulated swamped skiff and Panga skiff. Overlaid is the actual track of the whale remains for the same period.
Enlarge this image.Figure 6. Minimum distance of observed whale carcass to modelled potential drift path of the whale carcass based on horizontal dispersion coefficients of 5 m2/s and 10 m2/s for the modelled swamped skiff object 18–25 July 2023.
Ocean model product parameters. BOM (Bureau of Meteorology), NOAA (National Oceanic and Atmospheric Administration—National Centers for Environmental Prediction), ECMWF (European Centre for Medium-Range Weather Forecasts), and CMEMS (Copernicus Marine Environment Monitoring Service).
| Model | Provider | Horizontal | Vertical Coordinates | Forecast Length (h) | Time Step | Wind Forcing | Grid |
|---|---|---|---|---|---|---|---|
| Blue | BOM | 0.1° × 0.1° | 51 z layers | 96 | 3 | ACCESS-G | Global |
| HYCOM | NOAA | 1/12° (~9 km) | 32 hybrid layers | 144 | 3 | NOAA | Global |
| Copernicus | CMEMS | 0.083° × 0.083° (~9 km × ~9 km) | 75 layers | 240 | 1 | ECMWF | Global |
Outline of events and average drift speed of whale remains.
| Date | Time | Location of Whale Remains | Lat/Long | Distance Drifted (km) | Average Speed (km/h) | Activity on Whale Remains |
|---|---|---|---|---|---|---|
| 16 July 2023 | 4:00 p.m. | South of Noosa Heads | −26.48183 | - | - | First sighted by Coastguard |
| 17 July 2023 | 1:45 p.m. | North of Noosa Heads | −26.3402 | 26.2 | 1.2 | Sighted and fitted with tracker |
| 18 July 2023 | 7:09 a.m. | East of Cooloola beach | −26.17422 | 17.5 | 1.1 | Sighted and towed offshore |
| 18 July 2023 | 1:40 p.m. | Offshore of Coloola beach | −26.12883 | 27.5 | 4.1 | Repositioned offshore |
| 20 July 2023 | 1:04 p.m. | East of Double Island Point | −25.87401 | 37.3 | 0.8 | Loss of satellite tag signal for 11 h |
| 25 July 2023 | 3:00 a.m. | South of Fraser Island | −25.76318 | 114 | 0.7 | Loss of satellite tag signal |
Supplementary Materials
The following supporting information can be downloaded at:
References
1. Giardino, G.V.; Gana, J.C.; De León, M.C.; Mandiola, M.A.; Dassis, M.; Denuncio, P.; Elissamburu, A.; Morón, S.; Rodríguez Heredia, S.; Alvarez, C.K. Occurrence and anthropogenic-derived mortality of humpback whales (Megaptera novaeangliae) along the northern coast of Argentina, 2003–2021. N. Z. J. Mar. Freshw. Res.; 2022; 58, pp. 73-88. [DOI: https://dx.doi.org/10.1080/00288330.2022.2130365]
2. Vermeulen, E.; Jouve, E.; Best, P.; Cliff, G.; Dicken, M.; Kotze, D.; McCue, S.; Meÿer, M.; Seakamela, M.; Thompson, G. Mortalities of southern right whales (Eubalaena australis) and related anthropogenic factors in South African waters, 1999–2019. J. Cetacean Res. Manag.; 2022; 23, pp. 149-169. [DOI: https://dx.doi.org/10.47536/jcrm.v23i1.357]
3. van Weelden, C.; Towers, J.R.; Bosker, T. Impacts of climate change on cetacean distribution, habitat and migration. Clim. Chang. Ecol.; 2021; 1, 100009. [DOI: https://dx.doi.org/10.1016/j.ecochg.2021.100009]
4. Parsons, E.; Dolman, S.J.; Wright, A.J.; Rose, N.A.; Burns, W. Navy sonar and cetaceans: Just how much does the gun need to smoke before we act?. Mar. Pollut. Bull.; 2008; 56, pp. 1248-1257. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2008.04.025] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/18534632]
5. Moore, M.J.; Mitchell, G.H.; Rowles, T.K.; Early, G. Dead cetacean? Beach, bloat, float, sink. Front. Mar. Sci.; 2020; 7, 333. [DOI: https://dx.doi.org/10.3389/fmars.2020.00333]
6. Tucker, J.P.; Santos, I.R.; Crocetti, S.; Butcher, P. Whale carcass strandings on beaches: Management challenges, research needs, and examples from Australia. Ocean Coast. Manag.; 2018; 163, pp. 323-338. [DOI: https://dx.doi.org/10.1016/j.ocecoaman.2018.07.006]
7. Quaggiotto, M.-M.; Sánchez-Zapata, J.A.; Bailey, D.M.; Payo-Payo, A.; Navarro, J.; Brownlow, A.; Deaville, R.; Lambertucci, S.A.; Selva, N.; Cortés-Avizanda, A. Past, present and future of the ecosystem services provided by cetacean carcasses. Ecosyst. Serv.; 2022; 54, 101406. [DOI: https://dx.doi.org/10.1016/j.ecoser.2022.101406]
8. Tucker, J.P.; Santos, I.R.; Davis, K.L.; Butcher, P.A. Whale carcass leachate plumes in beach groundwater: A potential shark attractant to the surf?. Mar. Pollut. Bull.; 2019; 140, pp. 219-226. [DOI: https://dx.doi.org/10.1016/j.marpolbul.2019.01.043] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30803637]
9. Heiss, J.W. Whale burial and organic matter impacts on biogeochemical cycling in beach aquifers and leachate fluxes to the nearshore zone. J. Contam. Hydrol.; 2020; 233, 103656. [DOI: https://dx.doi.org/10.1016/j.jconhyd.2020.103656]
10. Clua, E.; Chauvet, C.; Read, T.; Werry, J.M.; Lee, S.Y. Behavioural patterns of a tiger shark (Galeocerdo cuvier) feeding aggregation at a blue whale carcass in Prony Bay, New Caledonia. Mar. Freshw. Behav. Physiol.; 2013; 46, pp. 1-20. [DOI: https://dx.doi.org/10.1080/10236244.2013.773127]
11. Nowacek, D.P.; Johnson, M.P.; Tyack, P.L.; Shorter, K.A.; McLellan, W.A. Buoyant balaenids: The ups and downs of buoyancy in right whales. Proc. R. Soc. Lond. Ser. B Biol. Sci.; 2001; 268, pp. 1811-1816. [DOI: https://dx.doi.org/10.1098/rspb.2001.1730] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/11522200]
12. Geraci, J.R.; Anderson, D.M.; Timperi, R.J.; Aubin, D.J.S.; Early, G.A.; Prescott, J.H.; Mayo, C.A. Humpback Whales (Megaptera novaeangliae) Fatally Poisoned by Dinoflagellate Toxin. Can. J. Fish. Aquat. Sci.; 1989; 46, pp. 1895-1898. [DOI: https://dx.doi.org/10.1139/f89-238]
13. Tønnessen, J.N.; Johnsen, A.O. The History of Modern Whaling; University of California Press: Berkeley, CA, USA, 1982.
14. Lea, J.S.E.; Daly, R.; Leon, C.; Daly, C.A.K.; Clarke, C.R. Life after death: Behaviour of multiple shark species scavenging a whale carcass. Mar. Freshw. Res.; 2019; 70, pp. 302-306. [DOI: https://dx.doi.org/10.1071/MF18157]
15. Curtis, T.H.; Kelly, J.T.; Menard, K.L.; Laroche, R.K.; Jones, R.E.; Klimley, A.P. Observations on the behavior of white sharks scavenging from a whale carcass at Point Reyes, California. Calif. Fish Game; 2006; 92, 113.
16. Fallows, C.; Gallagher, A.J.; Hammerschlag, N. White sharks (Carcharodon carcharias) scavenging on whales and its potential role in further shaping the ecology of an apex predator. PLoS ONE; 2013; 8, e60797. [DOI: https://dx.doi.org/10.1371/journal.pone.0060797] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23585850]
17. 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, pp. 1518-1531. [DOI: https://dx.doi.org/10.1071/MF16222]
18. Daniel, P.; Jan, G.; Cabioc’h, F.; Landau, Y.; Loiseau, E. Drift modeling of cargo containers. Spill Sci. Technol. Bull.; 2002; 7, pp. 279-288. [DOI: https://dx.doi.org/10.1016/S1353-2561(02)00075-0]
19. Peltier, H.; Dabin, W.; Daniel, P.; Van Canneyt, O.; Dorémus, G.; Huon, M.; Ridoux, V. The significance of stranding data as indicators of cetacean populations at sea: Modelling the drift of cetacean carcasses. Ecol. Indic.; 2012; 18, pp. 278-290. [DOI: https://dx.doi.org/10.1016/j.ecolind.2011.11.014]
20. Nero, R.W.; Cook, M.; Coleman, A.T.; Solangi, M.; Hardy, R. Using an ocean model to predict likely drift tracks of sea turtle carcasses in the north central Gulf of Mexico. Endanger. Species Res.; 2013; 21, pp. 191-203. [DOI: https://dx.doi.org/10.3354/esr00516]
21. Małyszko, M. Assessment of the potential effectiveness of the WIG craft in search action at sea using SARMAP software. TransNav Int. J. Mar. Navig. Saf. Sea Transp.; 2019; 13, pp. 437-442. [DOI: https://dx.doi.org/10.12716/1001.13.02.23]
22. Bell, M.; Charles-Edwards, E.; Wilson, T.; Cooper, J. Demographic futures for South East Queensland. Aust. Plan.; 2010; 47, pp. 126-134. [DOI: https://dx.doi.org/10.1080/07293682.2010.509028]
23. Heidemann, H.; Ribbe, J. Marine Heat Waves and the Influence of El Niño off Southeast Queensland, Australia. Front. Mar. Sci.; 2019; 6, 56. [DOI: https://dx.doi.org/10.3389/fmars.2019.00056]
24. Oke, P.R.; Roughan, M.; Cetina-Heredia, P.; Pilo, G.S.; Ridgway, K.R.; Rykova, T.; Archer, M.R.; Coleman, R.C.; Kerry, C.G.; Rocha, C. et al. Revisiting the circulation of the East Australian Current: Its path, separation, and eddy field. Prog. Oceanogr.; 2019; 176, 102139. [DOI: https://dx.doi.org/10.1016/j.pocean.2019.102139]
25. Azis Ismail, M.F.; Ribbe, J.; Karstensen, J.; Lemckert, C.; Lee, S.; Gustafson, J. The Fraser Gyre: A cyclonic eddy off the coast of eastern Australia. Estuar. Coast. Shelf Sci.; 2017; 192, pp. 72-85. [DOI: https://dx.doi.org/10.1016/j.ecss.2017.04.031]
26. Hunt, S.; Stuart, G.; Reed, R.; Mirfanderesk, H.; Tomlinson, R. Managing Coastal Disasters on Australia’s Gold Coast. Solutions to Coastal Disasters 2008; Amer Society of Civil Engineers: Reston, VA, USA, 2008; pp. 699-712.
27. Spaulding, M.L.; Isaji, T.; Hall, P.; Allen, A.A. A hierarchy of stochastic particle models for search and rescue (SAR): Application to predict surface drifter trajectories using HF radar current forcing. J. Mar. Environ. Eng.; 2006; 8, 181.
28. Spaulding, M.L.; Anderson, E.; Howlett, E.; Mendelsohn, D.; Opishinski, T. Application of OILMAP and SIMAP to predict the transport and fate of the North Cape Spill. Proceedings of the 19th Arctic and Marine Oil Spill Program, Technical Seminar; Calgary, AB, Canada, 12–14 June 1996.
29. Chu, T.-N.; Tsai, C.-H. Drift track simulation for past marine incidents using SARMAP. Proceedings of the OCEANS’10 IEEE SYDNEY; Sydney, Australia, 24–27 May 2010; pp. 1-4.
30. Spaulding, M.; Howlett, E. Application of SARMAP to estimate probable seach area for objects lost at sea. Oceanogr. Lit. Rev.; 1997; 5, 523.
31. Brushett, B.A.; King, B.A.; Lemckert, C. Evaluation of met-ocean forecast data effectiveness for tracking drifters deployed during operational oil spill response in Australian waters. J. Coast. Res.; 2011; 64, pp. 991-994.
32. Brushett, B.A.; King, B.A.; Lemckert, C.J. Assessment of ocean forecast models for search area prediction in the eastern Indian Ocean. Ocean Model.; 2016; 97, pp. 1-15. [DOI: https://dx.doi.org/10.1016/j.ocemod.2015.11.002]
33. Brushett, B.A.; Allen, A.A.; King, B.A.; Lemckert, C.J. Application of leeway drift data to predict the drift of panga skiffs: Case study of maritime search and rescue in the tropical pacific. Appl. Ocean Res.; 2017; 67, pp. 109-124. [DOI: https://dx.doi.org/10.1016/j.apor.2017.07.004]
34. Mu, L.; Tu, H.; Geng, X.; Qiao, F.; Chen, Z.; Jia, S.; Zhu, R.; Zhang, T.; Chen, Z. Research on the Drift Prediction of Marine Floating Debris: A Case Study of the South China Sea Maritime Drift Experiment. J. Mar. Sci. Eng.; 2024; 12, 357. [DOI: https://dx.doi.org/10.3390/jmse12020357]
35. Breivik, Ø.; Allen, A.A.; Maisondieu, C.; Olagnon, M. Advances in search and rescue at sea. Ocean Dyn.; 2013; 63, pp. 83-88. [DOI: https://dx.doi.org/10.1007/s10236-012-0581-1]
36. Davies, A. The numerical solution of the three-dimensional hydrodynamic equations, using a B-spline representation of the vertical current profile. Elsevier Oceanography Series; Elsevier: Amsterdam, The Netherlands, 1977; Volume 19, pp. 1-25.
37. Lellouche, J.-M.; Greiner, E.; Le Galloudec, O.; Garric, G.; Regnier, C.; Drevillon, M.; Benkiran, M.; Testut, C.-E.; Bourdalle-Badie, R.; Gasparin, F. Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time 1/12° high-resolution system. Ocean Sci.; 2018; 14, pp. 1093-1126. [DOI: https://dx.doi.org/10.5194/os-14-1093-2018]
38. Tucker, J.P.; Vercoe, B.; Santos, I.R.; Dujmovic, M.; Butcher, P.A. Whale carcass scavenging by sharks. Glob. Ecol. Conserv.; 2019; 19, e00655. [DOI: https://dx.doi.org/10.1016/j.gecco.2019.e00655]
39. Dicken, M. First observations of young of the year and juvenile great white sharks (Carcharodon carcharias) scavenging from a whale carcass. Mar. Freshw. Res.; 2008; 59, pp. 596-602. [DOI: https://dx.doi.org/10.1071/MF07223]
40. Reisdorf, A.G.; Bux, R.; Wyler, D.; Benecke, M.; Klug, C.; Maisch, M.W.; Fornaro, P.; Wetzel, A. Float, explode or sink: Postmortem fate of lung-breathing marine vertebrates. Palaeobiodivers. Palaeoenviron.; 2012; 92, pp. 67-81. [DOI: https://dx.doi.org/10.1007/s12549-011-0067-z]
41. Dudley, S.F.J.; Anderson-Reade, M.D.; Thompson, G.; McMullen, P.B.; Sharks, N. Concurrent scavenging off a whale carcass by great white sharks, Carcharodon carcharias, and tiger sharks, Galeocerdo cuvier. Fish. Bull.-Natl. Ocean. Atmos. Adm.; 2000; 98, pp. 646-649.
42. Lockyer, C. Body weights of some species of large whales. ICES J. Mar. Sci.; 1976; 36, pp. 259-273. [DOI: https://dx.doi.org/10.1093/icesjms/36.3.259]
43. Ward, S.; Robins, P.; Owen, A.; Demmer, J.; Jenkins, S. The importance of resolving nearshore currents in coastal dispersal models. Ocean Model.; 2023; 183, 102181. [DOI: https://dx.doi.org/10.1016/j.ocemod.2023.102181]
44. Meynecke, J.-O.; Samanta, S.; de Bie, J.; Seyboth, E.; Prakash Dey, S.; Fearon, G.; Vichi, M.; Findlay, K.; Roychoudhury, A.; Mackey, B. Do whales really increase the oceanic removal of atmospheric carbon?. Front. Mar. Sci.; 2023; 10, 1117409. [DOI: https://dx.doi.org/10.3389/fmars.2023.1117409]
45. Smith, C.R.; Bernardino, A.F.; Baco, A.; Hannides, A.; Altamira, I. Seven-year enrichment: Macrofaunal succession in deep-sea sediments around a 30 tonne whale fall in the Northeast Pacific. Mar. Ecol. Prog. Ser.; 2014; 515, pp. 133-149. [DOI: https://dx.doi.org/10.3354/meps10955]
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
; Zigic, Sasha 2 ; Perez, Larissa 2 ; Dunn, Ryan J K 2 ; Benfer, Nathan 2 ; Gustafson, Johan 3
; Bosshard, Simone 4 1 Whales & Climate Research Program, Griffith University, Gold Coast, QLD 4222, Australia; Centre for Coastal and Marine Research, Griffith University, Gold Coast, QLD 4222, Australia; Humpbacks & Highrises Inc., Gold Coast, QLD 4222, Australia
2 RPS Ocean Science and Technology, Gold Coast, QLD 4226, Australia
3 Centre for Coastal and Marine Research, Griffith University, Gold Coast, QLD 4222, Australia; School of Science, Technology and Engineering, University of the Sunshine Coast, Sippy Downs, QLD 4556, Australia
4 Sunshine Coast Council, Sunshine Coast, QLD 4560, Australia