Digging with ‘hands’: observations of food capture in the flying gurnard Dactylopterus volitans (Linnaeus, 1758)

ABSTRACT

Videofilms of a foraging flying gurnard (Dactylopterus volitans) were collected at Itaipu, Niterói, RJ, Brazil. Analysis revealed details of the use of anterior parts of the pectoral fins which act as digging ‘hands’ to access infaunal prey items that are subsequently captured by oral suction feeding. Each pectoral fin has two distinct sections articulated separately on the pectoral girdle. The digging ‘anterior pectoral fin’ mainly consists of segmented and flexible fin rays but has an anterior robust unsegmented ray that provides an edge to the ‘hand’, allowing penetration of the substratum. The huge ‘posterior pectoral fins’ are supported by unsegmented rays. Most digging episodes involved one ‘hand’ and consisted of 1–7 cycles of movement with frequencies 1.15–3.74 cycles s^?1. During a cycle, the ‘hand’ is moved forwards and medially above the substratum, then is twisted medially and simultaneously depressed so that the anterior unsegmented ray impacts and enters the substratum. The hand is then drawn backwards and laterally to disturb the substratum. To prevent upward pitching of the head during digging, the ‘posterior pectoral fins’ are both moved anteriorly and laterally to shift the centre of gravity forwards while the caudal and ?second dorsal fins continue to provide propulsive force.     

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We develop a semi‐structural model for forecasting inflation in the UK in which the New Keynesian Phillips curve (NKPC) is augmented with a time series model for marginal cost. By combining structural and time series elements we hope to reap the benefits of both approaches, namely the relatively better forecasting performance of time series models in the short run and a theory‐consistent economic interpretation of the forecast coming from the structural model. In our model we consider the hybrid version of the NKPC and use an open‐economy measure of marginal cost. The results suggest that our semi‐structural model performs better than a random‐walk forecast and most of the competing models (conventional time series models and strictly structural models) only in the short run (one quarter ahead) but it is outperformed by some of the competing models at medium and long forecast horizons (four and eight quarters ahead). In addition, the open‐economy specification of our semi‐structural model delivers more accurate forecasts than its closed‐economy alternative at all horizons. Copyright © 2014 John Wiley & Sons, Ltd.     

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