Optimal migration energetics of humpback whales and the implications of disturbance.

Whales migrate long distances and reproduce on a finite store of energy. Budgeting the use of this limited energy reserve is an important factor to ensure survival over the period of migration and to maximize reproductive investment. For some whales, migration routes are closely associated with coastal areas, exposing animals to high levels of human activity. It is currently unclear how various forms of human activity may disturb whales during migration, how this might impact their energy balance and how this could translate into long-term demographic changes. Here, we develop a theoretical bioenergetic model for migrating humpback whales to investigate the optimal migration strategy that minimizes energy use. The average migration velocity was an important driver of the total energy used by a whale, and an optimal velocity of 1.1 m s(-1) was determined. This optimal velocity is comparable to documented observed migration speeds, suggesting that whales migrate at a speed that conserves energy. Furthermore, the amount of resting time during migration was influenced by both transport costs and feeding rates. We simulated hypothetical disturbances to the optimal migration strategy in two ways, by altering average velocity to represent changes in behavioural activity and by increasing total travelled distance to represent displacement along the migration route. In both cases, disturbance increased overall energy use, with implications for the growth potential of calves.

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.