Estimating cetacean carrying capacity based on spacing behaviour.

Conservation of large ocean wildlife requires an understanding of how they use space. In Western Australia, the humpback whale (Megaptera novaeangliae) population is growing at a minimum rate of 10% per year. An important consideration for conservation based management in space-limited environments, such as coastal resting areas, is the potential expansion in area use by humpback whales if the carrying capacity of existing areas is exceeded. Here we determined the theoretical carrying capacity of a known humpback resting area based on the spacing behaviour of pods, where a resting area is defined as a sheltered embayment along the coast. Two separate approaches were taken to estimate this distance. The first used the median nearest neighbour distance between pods in relatively dense areas, giving a spacing distance of 2.16 km (± 0.94). The second estimated the spacing distance as the radius at which 50% of the population included no other pods, and was calculated as 1.93 km (range: 1.62-2.50 km). Using these values, the maximum number of pods able to fit into the resting area was 698 and 872 pods, respectively. Given an average observed pod size of 1.7 whales, this equates to a carrying capacity estimate of between 1187 and 1482 whales at any given point in time. This study demonstrates that whale pods do maintain a distance from each other, which may determine the number of animals that can occupy aggregation areas where space is limited. This requirement for space has implications when considering boundaries for protected areas or competition for space with the fishing and resources sectors

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

The carrying capacity estimates for method 1 (median nearest neighbour) and method 2 (50% of population with a pod within this radius).

<p>CC: Carrying capacity.</p><p>The carrying capacity of pods was calculated by fitting the maximum number of pods, including their radius distance, into the convex hull area encompassing the entire population. The carrying capacity of whales is the number of pods multiplied by the mean pod size.</p

A comparison of nearest neighbour distances with proximity to the centre of aggregation.

<p>The nearest neighbour distance (mean of flights ± standard error) of groups of pods based on how close they are to the centre of aggregation, i.e. the 10% mark contains the closest 10% pods to the mean, the 20% mark contains the closest 10–20%, and so on up to the 90–100% group. The only group with a significantly different nearest neighbour distance was the 90–100%, which was much higher than the rest.</p

The proportion of the population with a pod within a fixed radius, and increasing radii.

<p>Cumulative density plots of the proportion of population that have at least one pod within a specified radius, at increasing radii, for A) flight 1, B) flight 2, C) flight 3, D) flight 7, E) flight 9, and F) flight 10. Each plot was fit with an exponential curve using the least squares method, and the radius at which half the population have a pod within this radius was calculated from the curves. Theses radii are A) 2.09 km, B) 1.95 km, C) 2.50 km, D) 1.82 km, E) 1.61 km, and F) 1.62 km.</p

The aerial survey track over Exmouth Gulf.

<p>A typical course flown by the aircraft during surveys. This flight path was split into nine parallel transects spaced approximately 10 km apart.</p

The relationship between density and occupancy of whales in Exmouth Gulf.

<p>The total area occupied was calculated as the convex hull area for each flight, and the density as number of whales per km² in this area. The pattern emerging is that of a constant area used with increasing density, as highlighted by the grey shaded area. One survey (flight 5), marked as an open circle, is an outlier to this pattern.</p

The temporal changes in number of A) total whales, and B) calves, in Exmouth Gulf.

<p>A) For each flight, the total number of whales resident in Exmouth Gulf was estimated using distance sampling. The error bars mark the 95% confidence interval, calculated using a bootstrap in Distance 6.0. There is clear temporal pulse of whales in the Gulf, with the peak occupancy towards the end of September. B) The total number of calves observed during each survey flight also displays a temporal pulse to occupancy, but the peak here is slightly later in the first week of October.</p

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