Fishing and echolocation behavior of the greater bulldog bat,Noctilio leporinus,in the field

When hunting for fish Noctilio leporinus uses several strategies. In high search flight it flies within 20–50 cm of the water surface and emits groups of two to four echolocation signals, always containing at least one pure constant frequency (CF) pulse and one mixed CF-FM pulse consisting of a CF component which is followed by a frequency-modulated (FM) component. The pure CF signals are the longest, with an average duration of 13.3 ms and a maximum of 17 ms. The CF component of the CF-FM signals averages 8.9 ms, the FM sweeps 3.9 ms. The CF components have frequencies of 52.8–56.2 kHz and the FM components have an average bandwidth of 25.9 kHz. A bat in high search flight reacts to jumping fish with pointed dips at the spot where a fish has broken the surface. As it descends to the water surface the bat shows the typical approach pattern of all bats with decreasing pulse duration and pulse interval. A jumping fish reveals itself by a typical pattern of temporary echo glints, reflected back to the bat from its body and from the water disturbance. In low search flight N. leporinus drops to a height of only 4–10 cm, with body parallel to the water, legs extended straight back and turned slightly downward, and feet cocked somewhat above the line of the legs and poised within 2–4 cm of the water surface. In this situation N. leporinus emits long series of short CF-FM pulses with an average duration of 5.6 ms (CF 3.1 and FM 2.6) and an average pulse interval of 20 ms, indicating that it is looking for targets within a short range. N. leporinus also makes pointed dips during low search flight by rapidly snapping the feet into the water at the spot where it has localized a jumping fish or disturbance. In the random rake mode, N. leporinus drops to the water surface, lowers its feet and drags its claws through the water in relatively straight lines for up to 10m. The echolocation behavior is similar to that of high search flight. This indicates that in this hunting mode N. leporinus is not pursuing specific targets, and that raking is a random or statistical search for surface fishes. When raking, the bat uses two strategies. In directed random rake it rakes through patches of water where fish jumping activity is high. Our interpretation is that the bat detects this activity by echolocation but prefers not to concentrate on a single jumping fish. In the absence of jumping fish, after flying for several minutes without any dips, N. leporinus starts to make very long rakes in areas where it has hunted successfully before (memory-directed random rake). Hunting bats caught a fish approximately once in every 50–200 passes through the hunting area.     

Recruits of the stingless bee Scaptotrigona pectoralis learn food odors from the nest atmosphere

The ability to learn food odors inside the nest and to associate them with food sources in the field is of essential importance for the recruitment of nestmates in social bees. We investigated odor learning by workers within the hive and the influence of these odors on their food choice in the field in the stingless bee Scaptotrigona pectoralis. During the experiments, recruited bees had to choose between two feeders, one with an odor that was present inside the nest during the recruitment process, and one with an unknown odor. In all experiments with different odor combinations (linalool/phenylacetaldehyde, geraniol/eugenol) a significant majority of bees visited the feeder with the odor they had experienced in their nest (χ ²-tests; p?<?0.05). By contrast, the bees showed no preference for one of two feeders when they were either baited with the same odor (linalool) or contained no odor. Our results clearly show that naïve workers of S. pectoralis can learn the odor of a food source during the recruitment process from the nest atmosphere and that their subsequent food search in the field is influenced by the learned odor.     

Time and cost characterisation of emissions from non-road diesel equipment for infrastructure projects

The construction process contributes to pollutant emissions, particularly through the operation of diesel- and gasoline-powered equipment. In the past decade, a series of investigations were undertaken to quantify these emissions for a variety of non-road construction equipment performing different activities and undergoing different duty cycles, and a model to estimate quantities of six types of pollutant was developed. This paper uses that model to estimate emissions for four street and utility construction projects which no one has done previously. We combined information from company records with standard construction industry manuals to estimate total emissions for the projects and to examine the pollution patterns and magnitudes. The street construction projects all had similar emission profiles with a large peak at the beginning and a steady output of emissions throughout the duration of the project. For example, in two of the projects studied, half of all CO₂ emissions were produced before the projects were 40% completed. Results showed that demolition and earthwork are the activities with the largest contribution. The equipment types with the largest contribution are backhoes, front-end loaders, bulldozers and trenchers. Trenchers, for example, produced 30% of all emissions on the projects on which they were used.     

The Bhopal gas leak: Analyses of causes and consequences by three different models

The Bhopal Gas Leak, India 1984 is the largest chemical industrial accident ever. Haddon's and Berger's models for injury analysis have been tested, together with the project planning tool Logical Framework Approach (LFA).

The three models provide the same main message: That irrespectively of the direct cause to the leakage, it is only two parties that are responsible for the magnitude of the disaster: Union Carbide Corporation and the Governments of India and Madhya Pradesh. The models give somewhat different images of the process of the accident.

Models developed for analysis of injuries can be used for analysing a complicated mega accident like the Bhopal gas leak, although different models might stress different aspects.