Seasonal variations in prey selection by estuarine black-headed gulls (Larus ridibundus)

The number of black-headed gulls (Larus ridibundus) in the Clyde Estuary is large. In summer the average density has reached 1350 gulls km^?2 and in winter 180 gulls km^?2. This paper compares prey selection and feeding efficiency in gulls during summer and winter on tidal flats, and considers how seasonal differences may be adaptations to cope with seasonal changes in prey availability.Gross and net rates of energy intake were highest in summer because gulls captured more of the polychaete N. diversicolor than the amphipod C. volutator. In winter, gulls selected for C. volutator and therefore an energetically less profitable diet. Throughout the year gulls selected more C. volutator relative to N. diversicolor than expected on energetic grounds and so apparently did not maximize potential net rate of energy intake.Gulls used three techniques to capture prey and made most intensive use of the ‘crouch’ technique. Crouching gulls attained a much higher net rate of energy intake than ‘upright’ or ‘paddling’ gulls.A log-linear model showed that (a) season, water depth and gull density determined feeding technique and (b) feeding technique and season independently determined foraging success and prey selection. Thus gull density and water depth acted on prey selection through imposed variations in feeding technique.Reasons for gulls selecting energetically unprofitable C. volutator and for the use of several distinct feeding techniques are discussed.     

A neural network approach to ship track-keeping control

This paper presents an on-line trained neural net work controller for ship track-keeping problems. Following a brief review of the ship track-keeping control development since the 1980's, an analysis of various existing backpropagation-based neural controllers is provided. We then propose a single-input multioutput (SIMO) neural control strategy for situations where the exact mathematical dynamics of the ship are not available. The aim of this study is to build an autonomous neural controller which uses rudder to regulate both the tracking error and heading error. During the whole control process, the proposed SIMO neural controller adapts itself on-line from a direct evaluation of the control accuracy, and hence the need for a “teacher” or an off-line training process can be removed. With a relatively modest amount of quantitative knowledge of the ship behavior, the design philosophy enables real time control of a nonlinear ship model under random wind disturbances and measurement noise. Three different track-keeping tasks have been simulated to demonstrate the effectiveness of the training method and the robust performance of the proposed neural control strategy     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

Variations in the natural abundance of 15N in estuarine suspended particulate matter: A specific indicator of biological processing

In this study, the ¹⁴N:¹⁵N ratio of suspended particulate material collected from the Tamar river estuary, south-west England, is described. Three populations of particles, distinguishable by their ¹⁵N content, were observed. This investigation has shown that populations of estuarine particles are generated by biological transformations in situ and that the ¹⁵N content of estuarine particles does not merely reflect hydrodynamic mixing of the freshwater and seawater source particulate material.     

A simple model for lensing by black holes in galactic nuclei

The lensing properties of the Plummer model with a central point mass and external shear are derived, including the image multiplicities, critical curves and caustics. This provides a simple model for a flattened galaxy with a central supermassive black hole. For the Plummer model with black hole, the maximum number of images is four, provided the black hole mass is less than an upper bound which is calculated analytically. This introduces a method to constrain black hole masses by counting images, thus applicable at cosmological distance. With shear, the maximum number of images is six and we illustrate the occurrence of an astroid caustic and two metamorphoses.     

Particulate organic matter in the coastal and estuarine waters of Goa and its relationship with phytoplankton production

In the coastal and estuarine waters of Goa, particulate organic carbon (POC) varied from 0.52 to 2.51 mg l^?1 and from 0.28 to 5.24 mg l^?1 and particulate phosphorus (PP) varied from 0.71 to 5.18 μg l^?1 and from 0.78 to 20.34 μg l^?1, respectively. The mean values of chlorophyll and primary productivity were 1.94 mg m^?3 and 938.1 mg C m^?2 day^?1 in the coastal waters and 4.3 mg m^?3 and 636.5 mg C m^?1 day^?1 in the estuarine waters, respectively.$\text{POC}\text{chl}$ ratios were low in June and October even when POC values were quite high. The POC in surface waters was linearly correlated with the chlorophyll content. Also PP increased when chlorophyll and primary productivity remained high. The results suggest that the phytoplankton was sharply increasing and contributed to POC and PP content. The percentage of detritus calculated from the intercept values of chlorophyll on POC varied from 46 to 76% depending on season. Results indicate that the major portion of POC and PP during postmonsoon (October–January) is derived from phytoplankton production while the allochthonous matter predominate during monsoon (June–September).