A variable radius niching technique for speciation in genetic algorithms

In this paper, a continuation of a variable radius niche technique called Dynamic Niche Clustering developed by (Gan & Warwick, 1999) is presented. The technique employs a separate dynamic population of overlapping niches that coexists alongside the normal population. An empirical analysis of the updated methodology on a large group of standard optimisation test-bed functions is also given. The technique is shown to perform almost as well as standard fitness sharing with regards to stability and the accuracy of peak identification, but it outperforms standard fitness sharing with regards to time complexity. It is also shown that the technique is capable of forming niches of varying size depending on the characteristics of the underlying peak that the niche is populating.

Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: a case study

Flood extents caused by fluvial floods in urban and rural areas may be predicted by hydraulic models. Assimilation may be used to correct the model state and improve the estimates of the model parameters or external forcing. One common observation assimilated is the water level at various points along the modelled reach. Distributed water levels may be estimated indirectly along the flood extents in Synthetic Aperture Radar (SAR) images by intersecting the extents with the floodplain topography. It is necessary to select a subset of levels for assimilation because adjacent levels along the flood extent will be strongly correlated. A method for selecting such a subset automatically and in near real-time is described, which would allow the SAR water levels to be used in a forecasting model. The method first selects candidate waterline points in flooded rural areas having low slope. The waterline levels and positions are corrected for the effects of double reflections between the water surface and emergent vegetation at the flood edge. Waterline points are also selected in flooded urban areas away from radar shadow and layover caused by buildings, with levels similar to those in adjacent rural areas. The resulting points are thinned to reduce spatial autocorrelation using a top-down clustering approach. The method was developed using a TerraSAR-X image from a particular case study involving urban and rural flooding. The waterline points extracted proved to be spatially uncorrelated, with levels reasonably similar to those determined manually from aerial photographs, and in good agreement with those of nearby gauges.

Departures from convective equilibrium with a rapidly-varying surface forcing

Convective equilibrium is a long-standing and useful concept for understanding many aspects of the behaviour of deep moist convection. For example, it is often invoked in developing parameterizations for large-scale models. However, the equilibrium assumption may begin to break down as models are increasingly used with shorter timesteps and finer resolutions. Here we perform idealized cloud-system resolving model simulations of deep convection with imposed time variations in the surface forcing. A range of rapid forcing timescales from 1 − 36hr are used, in order to induce systematic departures from equilibrium. For the longer forcing timescales, the equilibrium assumption remains valid, in at least the limited sense that cycle-integrated measures of convective activity are very similar from cycle to cycle. For shorter forcing timescales, cycle-integrated convection becomes more variable, with enhanced activity on one cycle being correlated with reduced activity on the next, suggesting a role for convective memory. Further investigation shows that the memory does not appear to be carried by the domain-mean thermodynamic fields but rather by structures on horizontal scales of 5 − 20km. Such structures are produced by the convective clouds and can persist beyond the lifetime of the cloud, even through to the next forcing cycle.

Host selection and performance of the giant willow aphid, Tuberolachnus salignus (Gmelin) - Implications for pest management

1 The recent increase in planting of selected willow clones as energy crops for biomass production has resulted in a need to understand the relationship between commonly grown, clonally propagated genotypes and their pests. 2 For the first time, we present a study of the interactions of six willow clones and a previously unconsidered pest, the giant willow aphid Tuberolachnus salignus. 3 Tuberolachnus salignus alatae displayed no preference between the clones, but there was genetic variation in resistance between the clones; Q83 was the most resistant and led to the lowest reproductive performance in the aphid 4 Maternal effects buffered changes in aphid performance. On four tested willow clones fecundity of first generation aphids on the new host clone was intermediate to that of the second generation and that of the clone used to maintain the aphids in culture. 5 In the field, patterns of aphid infestation were highly variable between years, with the duration of attack being up to four times longer in 1999. In both years there was a significant effect of willow clone on the intensity of infestation. However, whereas Orm had the lowest intensity of infestation in the first year, Dasyclados supported a lower population level than other monitored clones in the second year.

Arable crop rotations under abiotic stress: a dynamic economic model

Break crops and multi-crop rotations are common in arable farm management, and the soil quality inherited from a previous crop is one of the parameters that determine the gross margin that is achieved with a given crop from a given parcel of land. In previous work we developed a dynamic economic model to calculate the potential yield and gross margin of a set of crops grown in a selection of typical rotation scenarios, and we reported use of the model to calculate coexistence costs for GM maize grown in a crop rotation. The model predicts economic effects of pest and weed pressures in monthly time steps. Validation of the model in respect of specific traits is proceeding as data from trials with novel crop varieties is published. Alongside this aspect of the validation process, we are able to incorporate data representing the economic impact of abiotic stresses on conventional crops, and then use the model to predict the cumulative gross margin achievable from a sequence of conventional crops grown at varying levels of abiotic stress. We report new progress with this aspect of model validation. In this paper, we report the further development of the model to take account of abiotic stress arising from drought, flood, heat or frost; such stresses being introduced in addition to variable pest and weed pressure. The main purpose is to assess the economic incentive for arable farmers to adopt novel crop varieties having multiple ‘stacked’ traits introduced by means of various biotechnological tools available to crop breeders.