Genetic isolation and morphological divergence of Black Sea bottlenose dolphins

The Black Sea is a semi-enclosed body of water that differs from the adjacent Mediterranean Sea in terms of its biodiversity, oceanographical and ecological characteristics. There is growing international concern about pollution in the Black Sea and other anthropogenic threats to its fauna. The bottlenose dolphin (Tursiops truncatus) is one of three species of cetaceans living in the Azov-Black Sea basin. Despite considerable research on bottlenose dolphins elsewhere, the extent of human impacts on the Black Sea populations is unknown. Previous attempts to award special conservation status to Black Sea cetaceans have failed specifically because policy makers have viewed their ecological and evolutionary uniqueness as equivocal. This study assessed divergence between Black Sea, Mediterranean Sea and Atlantic Ocean bottlenose dolphins for 26 cranial measurements (n = 75 adult bottlenose dolphin skulls) and mitochondrial DNA (n = 99 individuals). Black Sea bottlenose dolphins are smaller than those in the Mediterranean, and possess a uniquely shaped skull. As in a previous study, we found the Black Sea population to be genetically distinct, with relatively low levels of mtDNA diversity. Population genetic models suggest that Black Sea bottlenose dolphins have so little gene flow with the Mediterranean due to historical isolation that they should be managed separately.

Past and present distribution, densities and movements of blue whales Balaenoptera musculus in the Southern Hemisphere and northern Indian Ocean

1. 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. 2. Sighting surveys included 7 480 450 km of effort plus 14 676 days with unmeasured effort. Groups usually consisted of solitary whales (65.2%) or pairs (24.6%); larger feeding aggregations of unassociated individuals were only rarely observed. Sighting rates (groups per 1000 km from many platform types) varied by four orders of magnitude and were lowest in the waters of Brazil, South Africa, the eastern tropical Pacific, Antarctica and South Georgia; higher in the Subantarctic and Peru; and highest around Indonesia, Sri Lanka, Chile, southern Australia and south of Madagascar. 3. Blue whales avoid the oligotrophic central gyres of the Indian, Pacific and Atlantic Oceans, but are more common where phytoplankton densities are high, and where there are dynamic oceanographic processes like upwelling and frontal meandering. 4. Compared with historical catches, the Antarctic (‘true’) subspecies is exceedingly rare and usually concentrated closer to the summer pack ice. In summer they are found throughout the Antarctic; in winter they migrate to southern Africa (although recent sightings there are rare) and to other northerly locations (based on acoustics), although some overwinter in the Antarctic. 5. Pygmy blue whales are found around the Indian Ocean and from southern Australia to New Zealand. At least four groupings are evident: northern Indian Ocean, from Madagascar to the Subantarctic, Indonesia to western and southern Australia, and from New Zealand northwards to the equator. Sighting rates are typically much higher than for Antarctic blue whales.

Cross-Layer Packet Size Optimization for Wireless Terrestrial, Underwater, and Underground Sensor Networks

In this paper, a cross-layer solution for packet size optimization in wireless sensor networks (WSN) is introduced such that the effects of multi-hop routing, the broadcast nature of the physical wireless channel, and the effects of error control techniques are captured. A key result of this paper is that contrary to the conventional wireless networks, in wireless sensor networks, longer packets reduce the collision probability. Consequently, an optimization solution is formalized by using three different objective functions, i.e., packet throughput, energy consumption, and resource utilization. Furthermore, the effects of end-to-end latency and reliability constraints are investigated that may be required by a particular application. As a result, a generic, cross-layer optimization framework is developed to determine the optimal packet size in WSN. This framework is further extended to determine the optimal packet size in underwater and underground sensor networks. From this framework, the optimal packet sizes under various network parameters are determined.