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Distribution of blue whales in all months based on catches (×), sightings (○), strandings (▵), acoustic records (□) and Discovery mark positions (▿). Grey is used for positions ≤1973 and black for >1973.
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Blue whale locations in the Southern Hemisphere and northern Indian Ocean were obtained from catches (303 239), sightings (4383 records of ≥8058 whales), strandings (103), Discovery marks (2191) and recoveries (95), and acoustic recordings.
Sighting surveys included 7 480 450 km of effort plus 14 676 days with unmeasured effort. Groups usually cons...
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Historically, the Seychelles archipelago was an opportunistic whaling ground for fleets en route to and from the Antarctic. Soviet whalers illegally killed 500 blue whales near the Seychelles in the 1960s. Since then, no dedicated research has occurred to understand the ecological importance of this region for blue whales. Based on opportunistic si...
While visual survey of whales requires substantial means for limited areas, passive acoustic monitoring (PAM) offers larger scale coverage for long periods and less costs. It usually provides information about species behavior, e.g. seasonal movements, but tools are needed to detail the individuals' behavior. From Indian Ocean in a mountainous area...
Blue whale locations in the Southern Hemisphere and northern Indian Ocean were obtained from catches (303,239), sightings (4,383 records of ≥8,058 whales), strandings (103), Discovery marks (2,191) and recoveries (95), and acoustic recordings. 2. Sighting surveys included 7,480,450 km of effort plus 14,676 days with unmeasured effort. 3. Groups usu...
Surveys were conducted off the southern coast of Sri Lanka in 2014 and 2015 to investigate
the distribution patterns of blue whales (Balaenoptera musculus spp.) in relation to current
shipping lanes, and further offshore. There have been several reported ship strikes of blue
whales in this area and the IWC Scientific Committee has recognised the po...
Citations
... 95% CI [.01, 1.0], and annually varying for the right-side model. Branch (2008) applied a 2:1 weighting to blue whale survival estimates from the Gulf of St. Lawrence (Ramp et al., 2006) and pygmy blue whale estimates (Branch et al., 2004) Hamabe et al. (2023) presented blue whale abundance estimates for IWC Areas IV and V based on JARPA and JARPAII line-transect data and, similar to our capture-recapture study, reported lower estimates of abundance than Branch et al. (2007) for the same seasons and areas. For the most recent survey season in Area IV with estimates from both Hamabe et al. (2023) and Branch et al. (2007), 1997/1998, the mean estimate from the JARPA data was 124 whales (Hamabe et al., 2023, (Branch et al., 2007, table 5). ...
... Branch (2008) applied a 2:1 weighting to blue whale survival estimates from the Gulf of St. Lawrence (Ramp et al., 2006) and pygmy blue whale estimates (Branch et al., 2004) Hamabe et al. (2023) presented blue whale abundance estimates for IWC Areas IV and V based on JARPA and JARPAII line-transect data and, similar to our capture-recapture study, reported lower estimates of abundance than Branch et al. (2007) for the same seasons and areas. For the most recent survey season in Area IV with estimates from both Hamabe et al. (2023) and Branch et al. (2007), 1997/1998, the mean estimate from the JARPA data was 124 whales (Hamabe et al., 2023, (Branch et al., 2007, table 5). Summarizing their overall results, Hamabe et al.'s (2023) mean estimate for the population of Antarctic blue whales in Areas IV and V combined has remained below 1000 individuals in recent years. ...
... Although the population growth rates of 11% estimated by the combined Pradel model was greater than the 8.2% estimated by Branch et al. (2007), examination of the POPAN annual abundances (Figures 3 and 4; Table S7) shows even higher growth rates at the start of the time series, with decreasing growth in the latter portion of the series. ...
Photo‐identifications of Antarctic blue whales ( Balaenoptera musculus intermedia ) collected from 2003/2004 to 2018/2019 were used in a capture–recapture analysis to estimate abundance and population growth rate for the circumpolar Antarctic. Two capture–recapture models, POPAN and Pradel, were applied to these data. Estimates of annual abundance and their variances from the left and right side photo data were inferred using multimodel averaging, weighted by corrected Akaike information criterion (AIC c ), of 26 model configurations with prespecified survival rates from .75 to 1.0. These estimates based on the left and right side databases were then combined using inverse‐variance averaging into single estimates for each year. The POPAN superpopulation estimate (total number of individuals present during the sampling period) was 3,506 whales, 95% confidence interval (CI) [2,107, 5,832]. The estimated abundance from the final year of the study in 2018/2019 was 1,817 whales, 95% CI [714, 4,624]. The abundance estimates in this study may be biased downwards due to capture heterogeneity as a result of unequal spatial sampling. Population growth rate estimates were 11% from Pradel and 10% from POPAN. These rates were within the confidence interval estimated by a previous study for Antarctic blue whale population growth rate.
... There is evidence that Antarctic blue whales undergo a low-to-high latitude migration, as indicated by the annual rise and fall of the population present in the Southern Ocean (Mackintosh 1966). In the 20 th century, during the austral winter whaling seasons, substantial numbers of Antarctic blue whales (>8000) were caught off the coasts of Angola, Namibia, and the southwest coast of South Africa (Branch et al. 2007b), but not elsewhere in temperate Southern Hemisphere waters, perhaps because low-latitude whaling was concentrated in coastal and continental shelf waters with less effort offshore. More recently, Antarctic blue whales have been acoustically detected in the eastern tropical Pacific, the central Indian Ocean, off Australia and northern New Zealand, as well as off the coasts of Namibia and Angola (Stafford et al. 2004, McDonald et al. 2006, Branch et al. 2007b, Samaran et al. 2013, Thomisch et al. 2019, Torterotot et al. 2020). ...
... In the 20 th century, during the austral winter whaling seasons, substantial numbers of Antarctic blue whales (>8000) were caught off the coasts of Angola, Namibia, and the southwest coast of South Africa (Branch et al. 2007b), but not elsewhere in temperate Southern Hemisphere waters, perhaps because low-latitude whaling was concentrated in coastal and continental shelf waters with less effort offshore. More recently, Antarctic blue whales have been acoustically detected in the eastern tropical Pacific, the central Indian Ocean, off Australia and northern New Zealand, as well as off the coasts of Namibia and Angola (Stafford et al. 2004, McDonald et al. 2006, Branch et al. 2007b, Samaran et al. 2013, Thomisch et al. 2019, Torterotot et al. 2020). However, Antarctic blue whale calls are detected in the Southern Ocean year-round, which may indicate that some individuals remain in the Southern Ocean yearround, or that the timing of migration differs between individuals (Branch et al. 2007b, Širović et al. 2009, Thomisch et al. 2016. ...
... More recently, Antarctic blue whales have been acoustically detected in the eastern tropical Pacific, the central Indian Ocean, off Australia and northern New Zealand, as well as off the coasts of Namibia and Angola (Stafford et al. 2004, McDonald et al. 2006, Branch et al. 2007b, Samaran et al. 2013, Thomisch et al. 2019, Torterotot et al. 2020). However, Antarctic blue whale calls are detected in the Southern Ocean year-round, which may indicate that some individuals remain in the Southern Ocean yearround, or that the timing of migration differs between individuals (Branch et al. 2007b, Širović et al. 2009, Thomisch et al. 2016. Antarctic blue whale calls have also been heard in temperate waters off Namibia during the summer, providing additional evidence for variability in migration timing, or suggesting that some individuals skip migration and remain in temperate waters in summer (Thomisch et al. 2019). ...
Little is known about Antarctic blue whale ( Balaenoptera musculus intermedia ) movement and migration. In many baleen whales, distinct populations arose due to inherited fidelity to migration routes between breeding and feeding areas. To assess whether population structure is present in the form of feeding area fidelity in Antarctic blue whales, we analyzed historical Discovery mark-recovery data with a multistate model to estimate historical interyear movement rates among the 3 ocean basins in the Southern Ocean (Atlantic, Indian, and Pacific) during 1926-1963. We found high probabilities of interyear movement in almost all directions: for blue whales in the Atlantic basin of the Southern Ocean, we estimated that each year 15% (95% interval: 0.66-46%) moved to the Indian and 29% (4-49%) to the Pacific basins; from the Indian basin, 13% (3-33%) moved to the Atlantic and 32% (14-48%) to the Pacific basins; and from the Pacific basin, 28% (13-46%) moved to the Indian and 8% (0.9-24%) to the Atlantic basins. These high estimated movement rates provide little evidence for population structure arising from basin-specific feeding ground fidelity by Antarctic blue whales.
... Beluga whales vary in group size from small groups of two to ten individuals to large herds of 2,000 or more individuals [38][39][40], and thus visual detection of these amalgamated segments will need to be done after the identification using the semiautomated detection. However, this may be less of an issue for using OBIA on large solitary baleen whales [41,42]. One approach to rectify this limitation is to export the resulting shapefile into a GIS and separate features like this into two (or more) objects. ...
Very high-resolution (VHR) satellite imagery has proven to be useful for detection of large to medium cetaceans, such as odontocetes and offers some significant advantages over traditional detection methods. However, the significant time investment needed to manually read satellite imagery is currently a limiting factor to use this method across large open ocean regions. The objective of this study is to develop a semi-automated detection method using object-based image analysis to identify beluga whales (Delphinapterus leucas) in open water (summer) ocean conditions in the Arctic using panchromatic WorldView-3 satellite imagery and compare the detection time between human read and algorithm detected imagery. The false negative rate, false positive rate, and automated count deviation were used to assess the accuracy and reliability of various algorithms for reading training and test imagery. The best algorithm, which used spectral mean and texture variance attributes, detected no false positives and the false negative rate was low (<4%). This algorithm was able to accurately and reliably identify all the whales detected by experienced readers in the ice-free panchromatic image. The autodetection algorithm does have difficulty separately identifying whales that are perpendicular to one another, whales below the surface, and may use multiple segments to define a whale. As a result, for determining counts of whales, a reader should manually review the automated results. However, object-based image analysis offers a viable solution for processing large amounts of satellite imagery for detecting medium-sized beluga whales while eliminating all areas of the imagery which are whale-free. This algorithm could be adapted for detecting other cetaceans in ice-free water.
... The blue whale populations in the northern Indian Ocean are thought to be a subgroup of the pygmy blue whales (Balanoptera musculus) with some unique features compared to their Antarctic counterparts including a shorter length and different acoustic calls (de Vos et al., 2013). More importantly, unlike blue whales in other ocean basins, the Sri Lankan population is largely resident in these waters and does not undertake poleward migrations to feed (Branch et al., 2007;de Vos et al., 2013). This makes them particularly susceptible to stressors including tourism activities such as whalewatching and snorkelling. ...
Sri Lanka has emerged as a leading whale-watching destination, offering substantial economic benefits from its diverse cetacean species. The presence of year-round blue whale populations in Sri Lankan waters makes these species especially vulnerable to tourism-related stressors. While regulations are meant to oversee whale-watching, numerous operators participate in unlawful practices, contributing to a surge in swim-with-whale activities. This trend is driven by the tourism boom post-2020, compounded by inadequate governmental enforcement of existing regulations and a lack of awareness among tourists. This study investigates the impact of illegal swim-with-whale tours in Sri Lanka, focusing on the harmful effects of unethical practices. Key findings reveal widespread non-compliance, with 73% of operators in Mirissa and 83% of operators in Trincomalee engaging in illegal whale-swimming activities. Some operators encourage physical contact with whales. Despite regulations mandating a 100-meter distance, operators frequently approached within 2-3 meters, risking vessel collisions and behavioral disturbances. Offering to swim with whales has become a lucrative business as operators charge high prices while often evading taxes. Illegal operators focus on profit, charging significantly more and avoiding taxes, which leads to significant revenue losses for the government. Close encounters with whales endanger both wildlife and humans and compromise Sri Lanka's reputation as a sustainable tourism destination. The study provides insight into the current state of the whale watching industry in Sri Lanka , highlights the harmful impacts caused due to unethical and illegal swim with whale tours in the south and east of Sri Lanka and emphasizes the need for better enforcement of existing regulations and monitoring, for sustainable tourism.
... The blue whale populations in the northern Indian Ocean are thought to be a subgroup of the pygmy blue whales (Balanoptera musculus) with some unique features compared to their Antarctic counterparts including a shorter length and different acoustic calls (de Vos et al., 2013). More importantly, unlike blue whales in other ocean basins, the Sri Lankan population is largely resident in these waters and does not undertake poleward migrations to feed (Branch et al., 2007;de Vos et al., 2013). This makes them particularly susceptible to stressors including tourism activities such as whalewatching and snorkelling. ...
Sri Lanka has emerged as a leading whale-watching destination, offering substantial economic benefits from its diverse cetacean species. The presence of year-round blue whale populations in Sri Lankan waters makes these species especially vulnerable to tourism-related stressors. While regulations are meant to oversee whale-watching, numerous operators participate in unlawful practices, contributing to a surge in swim-with-whale activities. This trend is driven by the tourism boom post-2020, compounded by inadequate governmental enforcement of existing regulations and a lack of awareness among tourists. This study investigates the impact of illegal swim-with-whale tours in Sri Lanka, focusing on the effects of unethical practices. Key findings reveal widespread non-compliance, with 73% of operators in Mirissa and 83% of operators in Trincomalee engaging in illegal whale-swimming activities. Some operators encourage physical contact with whales. Despite regulations mandating a 100-meter distance, operators frequently approached within 2-3 meters, risking vessel collisions and behavioral disturbances. Offering to swim with whales has become a lucrative business as operators charge high prices while often evading taxes. Illegal operators focus on profit, charging significantly more and avoiding taxes, which leads to significant revenue losses for the government. Close encounters with whales endanger both wildlife and humans and compromise Sri Lanka's reputation as a sustainable tourism destination. The study provides insight into the current state of the whale watching industry in Sri Lanka , highlights the harmful impacts caused due to unethical and illegal swim with whale tours in the south and east of Sri Lanka and emphasizes the need for better enforcement of existing regulations and monitoring, for sustainable tourism.
... The blue whale populations in the northern Indian Ocean are thought to be a subgroup of the pygmy blue whales (Balanoptera musculus) with some unique features compared to their Antarctic counterparts including a shorter length and different acoustic calls (de Vos et al., 2013). More importantly, unlike blue whales in other ocean basins, the Sri Lankan population is largely resident in these waters and does not undertake poleward migrations to feed (Branch et al., 2007;de Vos et al., 2013). This makes them particularly susceptible to stressors including tourism activities such as whalewatching and snorkelling. ...
Sri Lanka has emerged as a leading whale-watching destination, offering substantial economic benefits from its diverse cetacean species. The presence of year-round blue whale populations in Sri Lankan waters makes these species especially vulnerable to tourism-related stressors. While regulations are meant to oversee whale-watching, numerous operators participate in unlawful practices, contributing to a surge in swim-with-whale activities. This trend is driven by the tourism boom post-2020, compounded by inadequate governmental enforcement of existing regulations and a lack of awareness among tourists. This study investigates the impact of illegal swim-with-whale tours in Sri Lanka, focusing on the effects of unethical practices. Key findings reveal widespread non-compliance, with 73% of operators in Mirissa and 83% of operators in Trincomalee engaging in illegal whale-swimming activities. Some operators encourage physical contact with whales. Despite regulations mandating a 100-meter distance, operators frequently approached within 2-3 meters, risking vessel collisions and behavioral disturbances. Offering to swim with whales has become a lucrative business as operators charge high prices while often evading taxes. Illegal operators focus on profit, charging significantly more and avoiding taxes, which leads to significant revenue losses for the government. Close encounters with whales endanger both wildlife and humans and compromise Sri Lanka's reputation as a sustainable tourism destination. The study provides insight into the current state of the whale watching industry in Sri Lanka , highlights the harmful impacts caused due to unethical and illegal swim with whale tours in the south and east of Sri Lanka and emphasizes the need for better enforcement of existing regulations and monitoring, for sustainable tourism.
... For example, the removal of minke whales probably led to competitive release of prey important also to penguins (krill, fish) and a coincident increase in numbers of trophically competing Adélie penguins (shown in Ballance et al. 2006). The International Whaling Commission enacted a moratorium on commercial whaling in [1985][1986], and since then only a few blue whales have been sighted in the Ross Sea region (Matsuoka et al. 2006, Branch et al. 2007, Miller et al. 2019. The number of minke whales in the Ross Sea and larger region, however, recovered by the 1990s (Branch 2006, Ainley 2010, despite a much lower 'scientific catch' that was allowed several years beyond the moratorium (since ceased). ...
Most of the Ross Sea has been designated a marine protected area (MPA), proposed 'to protect ecosystem structure and function'. To assess effectiveness, the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) selected Adélie (Pygoscelis adeliae) and emperor (Aptenodytes forsteri) penguins, Weddell seals (Leptonychotes weddellii) and Antarctic toothfish (Dissostichus mawsoni) as ecosystem change 'indicator species'. Stable for decades, penguin and seal populations increased during 1998-2018 to surpass historical levels, indicating that change in ecosystem structure and function is underway. We review historical impacts to population trends, decadal datasets of ocean climate and fishing pressure on toothfish. Statistical modelling for Adélie penguins and Weddell seals indicates that variability in climate factors and cumulative extraction of adult toothfish may explain these trends. These mesopredators, and adult toothfish, all prey heavily on Antarctic silverfish (Pleuragramma antarcticum). Toothfish removal may be altering intraguild predation dynamics, leading to competitive release of silverfish and contributing to penguin and seal population changes. Despite decades of ocean/weather change, increases in indicator species numbers around Ross Island only began once the toothfish fishery commenced. The rational-use, ecosystem-based viewpoint promoted by CCAMLR regarding toothfish management needs re-evaluation, including in the context of the Ross Sea Region MPA.
... Indian Ocean blue whale (B. m. indica) (Branch et al., 2007;Leslie et al., 2020;Samaran et al., 2013). A possible fifth subspecies has been observed off Chile (Branch et al., 2007;Leslie et al., 2020;Samaran et al., 2013), but it has not been officially recognized. ...
... m. indica) (Branch et al., 2007;Leslie et al., 2020;Samaran et al., 2013). A possible fifth subspecies has been observed off Chile (Branch et al., 2007;Leslie et al., 2020;Samaran et al., 2013), but it has not been officially recognized. The Australian population of pygmy blue whales has been shown to conduct regular migrations between the southern and western waters of Australia, the Savu Sea, Timor Sea, and Banda Sea (Double et al., 2014;Möller et al., 2020), while some videos uploaded in September 2016 and November 2018 suggest that the Banda Sea might be an important nursing ground for this subspecies (Pindito, 2016(Pindito, , 2018. ...
... To address this, Mangerud et al. (2006) used humans as a representation of all mammals with the caveat that unlike humans, whales continue growing throughout their lives. Humpback, fin, and blue whales all have estimated lifespans of 80-90 years (Chittleborough, 1965;Branch et al., 2007;Malige et al., 2022;Lockyer, 1977;Arrigoni et al., 2011). The whale bone reservoir age implies that the bone should reflect the sea reservoir age at the time in which the carbon was fixed in the collagen at the time of the whale's death (Mangerud et al., 2006). ...
... The SO, and in particular the Southern Boundary of the Antarctic Circumpolar Current (sbACC), is a known ecologically important region as high densities of krill are known to occur here, which forms the primary food resource for ABW (Atkinson et al., 2008;Tynan, 1998). The distribution of ABW is considered to be greatly influenced by prey availability, hence, the SO serves as an important (feeding) habitat for ABW (Branch, Stafford, et al., 2007;Thomisch et al., 2016). ABWs were once common in the SO, but more than 300,000 whales were hunted to near extinction in the Southern Hemisphere during the last century's industrial whaling (Clapham & Baker, 2009;Cooke, 2018;Miller et al., 2015). ...
... Visual-data models PAM-data models Combined-data models (Figures 1 and 3). up to South Georgia, is considered an important ABW feeding area during summer (Wiedenmann et al., 2011) and was the primary location of ABW commercial whaling (Branch, Stafford, et al., 2007;Kemp & Bennett, 1932;Leaper & Miller, 2011;Risting, 1928). ...
... Interestingly, in the Atlantic sector of the SO, the sbACC was predicted to be the northern limit of high HS area for all models. This strongly agrees with information from visual and catch data (Branch, Stafford, et al., 2007;Calderan et al., 2020;Tynan, 1998) as well as PAM studies (Shabangu et al., 2017;Širović et al., 2009). The sbACC has a critical ecological function in the SO ecosystem, influencing the distribution of many cetacean species, with areas close to it being seasonally associated with high primary production and krill abundance (Matsuoka et al., 2003;Tynan, 1998). ...
Aim: Species distribution models (SDMs) are essential tools in ecology and conservation. However, the scarcity of visual sightings of marine mammals in remote polar areas hinders the effective application of SDMs there. Passive acoustic monitoring (PAM) data provide year-round information and overcome foul weather limitations faced by visual surveys. However, the use of PAM data in SDMs has been sparse so far. Here, we use PAM-based SDMs to investigate the spatiotemporal distribution of the critically endangered Antarctic blue whale in the Weddell Sea.
Location: The Weddell Sea.
Methods: We used presence-only dynamic SDMs employing visual sightings and PAM detections in independent models. We compared the two independent models with a third combined model that integrated both visual and PAM data, aiming at leveraging the advantages of each data type: the extensive spatial extent of visual data and the broader temporal/environmental range of PAM data.
Results: Visual and PAM data prove complementary, as indicated by a low spatial overlap between daily predictions and the low predictability of each model at detections of other data types. Combined data models reproduced suitable habitats as given by both independent models. Visual data models indicate areas close to the sea ice edge (SIE) and with low-to-moderate sea ice concentrations (SIC) as suitable, while PAM data models identified suitable habitats at a broader range of distances to SIE and relatively higher SIC.
Main Conclusions: The results demonstrate the potential of PAM data to predict year-round marine mammal habitat suitability at large spatial scales. We provide reasons for discrepancies between SDMs based on either data type and give methodological recommendations on using PAM data in SDMs. Combining visual and PAM data in future SDMs is promising for studying vocalized animals, particularly when using recent advances in integrated distribution modelling methods.
