Parasitic isopod Anilocra apogonae, a drag for the cardinal fish Cheilodipterus quinquelineatus

Cymothoid isopods Anilocra apogonae are regular ectoparasites of the cardinal fish Cheilodipterus quinquelineatus on the Great Barrier Reef. To determine whether this large isopod, attached to the head of the fish, affects the physiology and behaviour of its host, we conducted morphological measurements to obtain a condition index and several laboratory experiments on fish with and without isopods. The condition index did not vary between parasitised and non-parasitised wild fish. However, we found that parasitised fish lost more weight than unparasitised fish when fed a low food ration. Parasitised fish also had a higher rate of oxygen consumption than non-parasitised fish. When maintaining body posture in calm water, parasitised fish had an elevated pectoral fin beat frequency, probably because the isopod attaches asymmetrically, causing an asymmetrical weight balance for which the fish needs to compensate. Moreover, the sustained aerobic swimming speed as well as the swimming endurance at high water speeds were reduced in parasitised fish, possibly because of the drag from the parasite. The results suggest that parasites can have significant effects on fish even if this is not revealed by their body condition index in the wild. The metabolic effects found imply that parasitised fish may have to spend more time foraging to compensate for their higher metabolism. This could expose them to a higher risk of being eaten, a situation made worse by an impaired swimming ability that may reduce their capacity to escape a predator.

Identification of MIMO Hammerstein systems using cardinal spline functions

A new approach to identify multivariable Hammerstein systems is proposed in this paper. By using cardinal cubic spline functions to model the static nonlinearities, the proposed method is effective in modelling processes with hard and/or coupled nonlinearities. With an appropriate transformation, the nonlinear models are parameterized such that the nonlinear identification problem is converted into a linear one. The persistently exciting condition for the transformed input is derived to ensure the estimates are consistent with the true system. A simulation study is performed to demonstrate the effectiveness of the proposed method compared with the existing approaches based on polynomials. (C) 2006 Elsevier Ltd. All rights reserved.