Construction of Nominal Ionospheric Gradient Using Satellite Pair Method Based on GNSS CORS Observation in Indonesia

Ground-Based Augmentation System (GBAS) is a GNSS augmentation system that meets International Civil Aviation Organization (ICAO) requirements to support precision approach and landing. GBAS is based on the local differential GNSS technique with reference stations located around the airport to provide necessary integrity and accuracy. The performance of the GBAS system can be affected by the gradient in the ionospheric delay between the aircraft and the reference stations. A nominal ionospheric gradient, which is bounded by a conservative error bound, is represented by a parameter σvig. σvig was commonly determined using station pair to GNSS Continuous Operating Reference Station (CORS) data. The station pair method is susceptible to doubling of receiver bias error and is not suitable with the CORS conditions in Indonesia. We propose a satellite pair method that is found to be more suitable for the CORS network over Indonesia which is centered in Java and Sumatra islands. The value of σvig (4.48 mm/km) is obtained using this method along with the preliminary results of a comparison of σvig from Java and Sumatra islands.

Biased generalization of salient traits drives the evolution of warning signals

The importance of receiver biases in shaping the evolution of many signalling systems is widely acknowledged. Here, we show that receiver bias can explain which traits evolve to become warning signals. For warning coloration, a generalization bias for a signalling trait can result from predators learning to discriminate unprofitable from profitable prey. However, because the colour patterns of prey are complex traits with multiple components, it is crucial to understand which of the many aspects of prey appearance evolve into signals. We provide experimental evidence that the more salient differences in prey traits give rise to greater generalization bias, corresponding to stronger selection towards trait exaggeration. Our results are based on experiments with domestic chickens as predators in a Skinner-box-like setting, and imply that the difference in appearance between profitable and unprofitable prey that is most rapidly learnt produces the greatest generalization bias. As a consequence, certain salient traits of unprofitable prey are selected towards exaggeration to even higher salience, driving the evolution of warning coloration. This general idea may also help to explain the evolution of many other striking signalling traits found in nature.