Pygmy blue whale movement, distribution and important areas in the Eastern Indian Ocean

This study was conducted as part of AIMS’ North West Shoals to Shore Research Program (NWSSRP) and was supported by Santos as part of the company’s commitment to better understand Western Australia’s marine environment. Hydrophone pressure data from Ocean Bottom Seismometers (OBS) were provided by the CANPASS project, jointly funded by the National Natural Science Foundation of China (NSFC grants 91955210, 41625016), and the China Academy of Science (CAS program GJHZ1776). Instruments were provided by the Australian National instrument pool ANSIR (http://ansir.org.au/). ANSIR, OBS data was also made data available from the Geoscience Australia and Shell. Data was sourced from Australia’s Integrated Marine Observing System (IMOS).Pygmy blue whales in the South-east Indian Ocean migrate from the southern coast of Australia to Indonesia, with a significant part of their migration route passing through areas subject to oil and gas production. This study aimed at improving our understanding of the spatial extent of the distribution, migration and foraging areas, to better inform impact assessment of anthropogenic activities in these regions. Using a combination of passive acoustic monitoring of the NW Australian coast (46 instruments from 2006 to 2019) and satellite telemetry data (22 tag deployments from 2009 to 2021) we quantified the pygmy blue whale distribution and important areas during their northern and southern migration. We show extensive use of slope habitat off Western Australia and only minimal use of shelf habitat, compared to southern Australia where use of the continental shelf and shelf break predominates. In addition, movement behaviour estimated by a state-space model on satellite tag data showed that in general pygmy blue whales off Western Australia were mostly engaged in migration, interspersed with mostly relatively short periods (median = 28hours, range = 2 – 1080hours) of low move persistence (slow movement with high turning angles), which is indicative of foraging. Using the spatial overlap of time and number of whales in area analysis of the satellite tracking data (top 50% of grid cells) with foraging movement behaviour, we quantified the spatial extent of pygmy blue whale high use areas for foraging and migration. We compared these areas to the previously described areas of importance to foraging and migrating whales (Biologically Important Areas; BIAs). In some cases these had good agreement with the most important areas we calculated from our data, but others had only low (5%) to moderate (13%) overlap. Month was the most important variable predicting the number of pygmy blue whale units and number of singers (acting as indices of pygmy blue whale density). Whale density was highest in the southern part of the NW Australian coast and whales were present there between April-June, and November-December, a pattern also confirmed by the satellite tracking data. Available data indicated pygmy blue whales spent up to 124 days in Indonesian waters (34% of annual cycle). Since this area may also be the calving ground for this population, inter-jurisdictional management is necessary to ensure their full protection.Publisher PDFPeer reviewe

Southern Hemisphere breeding stock 'D' humpback whale population estimates from North West Cape, Western Australia

Estimates of the abundance of breeding group ‘D’ humpback whales (Megaptera novaeangliae) are key to managing what is thought to be one of the largest populations of the species. Five years (2000, 2001, 2006, 2007, and 2008) of aerial surveys carried out over an eight-year period at North West Cape (NWC, Western Australia) using line transect methodology allowed trends in whale numbers to be investigated, and provided a base for comparison with estimates made approximately 400km south at Shark Bay (SB, Western Australia). A total of 3,127 whale detections were made during 74 surveys of the 7,043km2 study area west of NWC. Pod abundance for each flight was computed using a Horvitz-Thompson like estimator and converted to an absolute measure of population size after corrections were made for estimated mean cluster size, unsurveyed time, swimming speed and animal availability. Resulting estimates from the migration model of best fit with the most credible assumptions were 7,276 (CI = 4,993-10,167) for 2000, 12,280 (CI = 6,830-49,434) for 2001, 18,692 (CI = 12,980-24,477) for 2006, 20,044 (CI = 13,815-31,646) for 2007, and 26,100 (CI = 20,152-33,272) for 2008. Based on these data, the trend model with the greatest r2 was exponential with an annual increase rate of 13% (CI=5.6%-18.1%). While this value is above the species’ maximum plausible growth rate of 11.8%, it is reasonably close to previous reports of between 10-12%. The coefficient of variation, however, was too large for a reliable trend estimate. Perception bias was also not accounted for in these calculations. Based on a crude appraisal which yielded an estimated p(0) of 0.783 (0from independent observer effort, CV=0.973), the 2008 humpback population size could then be as large as 33,333. In conclusion, the work here provides evidence of an increasing breeding group ‘D’ humpback whale population, however more surveys are necessary to confirm whether the population is indeed increasing at its maximum rat

Pygmy Blue Whale Diving Behaviour Reflects Song Structure

Passive acoustic monitoring is increasingly employed to monitor whales, their population size, habitat usage, and behaviour. However, in the case of the eastern Indian Ocean pygmy blue whale (EIOPB whale), its applicability is limited by our lack of understanding of the behavioural context of sound production. This study explored the context of singing behaviour using a 7.6-day biotelemetry dataset from a single EIOPB whale moving north from 31.5° S to 28.5° S along the Western Australian coast and a simultaneously collected, but separate, acoustic recording. Diving behaviour was classified using an automated classification schema. Singing was identified in the depth, pitch, and fluking time series of the dive profile. The EIOPB whale sang profusely as it migrated, spending more time singing during the day (76.8%) than at night (64.9%), and most during twilight periods (83.3%). The EIOPB whale almost exclusively produced the three-unit (P3) song while milling. It sang the two-unit (P2) song in similar proportions to the P3 song while travelling, except at night when P3 was sung 2.7 times more than P2. A correlation between singing depth, migration duration, and water temperature provides a biological basis to explain depth preferences for sound production, which may contribute to the cause of intra- and inter-annual sound frequency trends

Genetic diversity and structure of blue whales (Balaenoptera musculus) in Australian feeding aggregations

The worldwide distribution of blue whales (Balaenoptera musculus) has not prevented this species from becoming endangered due to twentieth century whaling. In Australia there are two known feeding aggregations of blue whales, which most likely are the pygmy subspecies (B. m. brevicauda). It is unknown whether individuals from these feeding aggregations belong to one breeding stock, or multiple breeding stocks that either share or occupy separate feeding grounds. This was investigated using ten microsatellite loci and mitochondrial DNA control region sequences (N = 110). Both sets of markers revealed no significant genetic structure, suggesting that these whales are likely to belong to the same breeding stock.5 page(s

Marine seismic surveys - A study of environmental implications

© CSIRO 2000. An experimental program was run by the Centre for Marine Science and Technology of Curtin University between March 1996 and October 1999 to study the environmental implications of offshore seismic survey noise. This work was initiated and sponsored by the Australian Petroleum Production and Exploration Association. The program: characterised air gun signal measurements; modelled air gun array sources and horizontal air gun signal propagation; developed an 'exposure model' to predict the scale of potential biological effects for a given seismic survey over its duration; made observations of humpback whales traversing a 3D seismic survey; carried out experiments of approaching humpback whales with a single operating air gun; carried out trials with an air gun approaching a cage containing sea turtles, fishes or squid; and modelled the response of fish hearing systems to airgun signals. The generalised response of migrating humpback whales to a 3D seismic vessel was to take some avoidance manoeuvre at >4 km then to allow the seismic vessel to pass no closer than 3 km. Humpback pods containing cows which were involved in resting behaviour in key habitat types, as opposed to migrating animals, were more sensitive and showed an avoidance response estimated at 7−12 km from a large seismic source. Male humpbacks were attracted to a single operating air gun due to what was believed the similarity of an air gun signal and a whale breaching event (leaping clear of the water and slamming back in). Based on the response of captive animals to an approaching single air gun and scaling these results, indicated sea turtles displayed a general 'alarm' response at an estimated 2 km range from an operating seismic vessel and behaviour indicative of avoidance estimated at 1 km. Similar trials with captive fishes showed a generic fish 'alarm' response of swimming faster, swimming to the bottom, tightening school structure, or all three, at an estimated 2−5 km from a seismic source. Modelling the fish ear predicted that at ranges < 2 km from a seismic source the ear would begin a rapid increase in displacement parameters. Captive fish exposed to short range air gun signals were seen to have some damaged hearing structures, but showed no evidence of increased stress. Captive squid showed a strong startle response to nearby air gun start up and evidence that they would significantly alter their behaviour at an estimated 2−5 km from an approaching large seismic source

Marine seismic surveys: analysis and propagation of air-gun signals; and effects of exposure on humpback whales, sea turtles, fishes and squid.

An experimental program was run by the Centre for Marine Science and Technology of Curtin University between March 1996 and October 1999 to study the environmental implications of offshore seismic survey noise. This work was initiated and sponsored by the Australian Petroleum Production Exploration Association. The program: characterised air-gun signal measurements; modelled air-gun array sources and horizontal air-gun signal propagation; developed an 'exposure model' to predict the scale of potential biological effects for a given seismic survey over its duration; made observations of humpback whales traversing a 3D seismic survey; carried out experiments of approaching humpback whales with a single operating air-gun; carried out trials with an air-gun approaching a cage containing sea turtles, fishes or squid; and modelled the response of fish hearing systems to air-gun signals. The generalised response of migrating humpback whales to a 3D seismic vessel was to take some avoidance manoeuvre at > 4 km then to allow the seismic vessel to pass no closer than 3 km. Humpback pods containing cows which were involved in resting behaviour in key habitat types, as opposed to migrating animals, were more sensitive and showed an avoidance response estimated at 7-12 km from a large seismic source. Male humpbacks were attracted to a single operating air-gun due to what was believed the similarity of an air-gun signal and a whale breaching event (leaping clear of the water and slamming back in). Based on the response of captive animals in cold water to an approaching single air-gun and scaling these results, indicated sea turtles displayed a general 'alarm' response at an estimated 2 km range from an operating seismic vessel and behaviour indicative of avoidance estimated at 1 km. Similar trials with captive fishes showed a common fish 'alarm' response of swimming faster, swimming to the bottom, tightening school structure, or all three, at an estimated 2-5 km from a seismic source. Modelling the fish ear predicted that at ranges < 2 km from a seismic source the ear would begin a rapid increase in displacement parameters. Captive fish exposed to short range air-gun signals were seen to have some damaged hearing structures, but showed no evidence of increased stress. Captive squid showed a strong startle responses to nearby air-gun start up and evidence that they would significantly alter their behaviour at an estimated 2-5 km from an approaching large seismic source

Low genetic diversity in pygmy blue whales is due to climate-induced diversification rather than anthropogenic impacts

Unusually low genetic diversity can be a warning of an urgent need to mitigate causative anthropogenic activities. However, current low levels of genetic diversity in a population could also be due to natural historical events, including recent evolutionary divergence, or long-term persistence at a small population size. Here, we determine whether the relatively low genetic diversity of pygmy blue whales (Balaenoptera musculus brevicauda) in Australia is due to natural causes or overexploitation. We apply recently developed analytical approaches in the largest genetic dataset ever compiled to study blue whales (297 samples collected after whaling and representing lineages from Australia, Antarctica and Chile). We find that low levels of genetic diversity in Australia are due to a natural founder event from Antarctic blue whales (Balaenoptera musculus intermedia) that occurred around the Last Glacial Maximum, followed by evolutionary divergence. Historical climate change has therefore driven the evolution of blue whales into genetically, phenotypically and behaviourally distinct lineages that will likely be influenced by future climate change

Hybridization of Southern Hemisphere blue whale subspecies and a sympatric area off Antarctica : impacts of whaling or climate change?

Understanding the degree of genetic exchange between subspecies and populations is vital for the appropriate management of endangered species. Blue whales (Balaenoptera musculus) have two recognized Southern Hemisphere subspecies that show differences in geographic distribution, morphology, vocalizations and genetics. During the austral summer feeding season, the Antarctic blue whale (B. m. intermedia) is found in polar waters and the pygmy blue whale (B. m. brevicauda) in temperate waters. Here, we genetically analyzed samples collected during the feeding season to report on several cases of hybridization between the two recognized blue whale Southern Hemisphere subspecies in a previously unconfirmed sympatric area off Antarctica. This means the pygmy blue whales using waters off Antarctica may migrate and then breed during the austral winter with the Antarctic subspecies. Alternatively, the subspecies may interbreed off Antarctica outside the expected austral winter breeding season. The genetically estimated recent migration rates from the pygmy to Antarctic subspecies were greater than estimates of evolutionary migration rates and previous estimates based on morphology of whaling catches. This discrepancy may be due to differences in the methods or an increase in the proportion of pygmy blue whales off Antarctica within the last four decades. Potential causes for the latter are whaling, anthropogenic climate change or a combination of these and may have led to hybridization between the subspecies. Our findings challenge the current knowledge about the breeding behaviour of the world's largest animal and provide key information that can be incorporated into management and conservation practices for this endangered species.13 page(s