Genetic variation in foliar carbon isotope composition in relation to tree growth and foliar nitrogen concentration in clones of the F-1 hybrid between slash pine and Caribbean pine

The objectives of this study were: (1) to quantify the genetic variation in foliar carbon isotope composition (delta(13)C) of 122 clones of ca. 4-year-old F-1 hybrids between slash pine (Pinus elliottii Engelm var. elliottii) and Caribbean pine (Pinus caribaea var. hondurensis Barr.,et Golf.) grown at two field experimental sites with different water and nitrogen availability in southeast Queensland, Australia, in relation to tree growth and foliar nitrogen concentration (N-mass); and (2) to assess the potential of using delta(13)C measurements, in the foliage materials collected from the clone hedges at nursery and the 4-year-old tree canopies in the field, as an indirect index of tree water use efficiency for selecting elite F-1 hybrid pine clones with improved tree growth. There were significant differences in foliar delta(13)C between the nursery hedges and the 4-year-old tree canopies in the field, between the summer and winter seasons, between the two experimental sites, and between the upper outer and lower outer canopy positions sampled. This indicates that delta(13)C measurements in the foliage materials are significantly influenced by the sampling techniques and environmental conditions. Significant differences in foliar delta(13)C, at the upper outer canopy in both field experiments in summer and winter, were detected between the clones, and between the female parents of the clones. Clone means of tree height at age ca. 3 years were positively related to those of the upper outer canopy delta(13)C at both experimental sites in winter, but only for the wetter site in summer. There were positive, linear relationships between clone means of canopy delta(13)C and those of canopy N-mass, indicating that canopy photosynthetic capacity might be an important factor regulating the clonal variation in canopy delta(13)C. Significant correlations were found between clone means of canopy delta(13)C at both experimental sites in summer and winter, and between those at the upper outer and lower outer canopy positions. Mean clone delta(13)C for the nursery hedges was only positively related to mean clone stem diameter at 1.3 m height at age 3 years on the wetter site. The clone by site interaction for foliar delta(13)C at the upper outer canopy was significant only in summer. Overall, the relatively high genetic variance components for foliar delta(13)C and significant, positive correlations between clone means of foliar delta(13)C and tree growth have highlighted the potential of using foliar delta(13)C measurements for assisting in selection of the elite F-1 hybrid pine clones with improved tree growth. (C) 2002 Elsevier Science B.V. All rights reserved.

A genetic estimation algorithm for parameters of stochastic ordinary differential equations

A generic method for the estimation of parameters for Stochastic Ordinary Differential Equations (SODEs) is introduced and developed. This algorithm, called the GePERs method, utilises a genetic optimisation algorithm to minimise a stochastic objective function based on the Kolmogorov-Smirnov statistic. Numerical simulations are utilised to form the KS statistic. Further, the examination of some of the factors that improve the precision of the estimates is conducted. This method is used to estimate parameters of diffusion equations and jump-diffusion equations. It is also applied to the problem of model selection for the Queensland electricity market. (C) 2003 Elsevier B.V. All rights reserved.

Genetic control of adventitious rooting on stem cuttings in two Pinus elliottii x P-caribaea hybrid families

Genetic control of adventitious rooting was characterised in two unrelated Pinus elliottii x P. caribaea families, an outbred F-1 (n = 287) and an inbred F-2 ( n = 357). Rooting percentage was assessed in three settings and root biomass was measured on a sub-set of clones ( n = 50) from each family in the third setting. On average, clones in the outbred F-1 had a higher rooting percentage (mean +/- SE; 59 +/- 1.9%) and biomass (mean +/- SD; 0.41 +/- 0.24 g) than clones in the inbred F-2 family ( mean +/- SE; 48 +/- 1.8% and mean +/- SD; 0.19 +/- 0.13 g). Genetic determination for rooting percentage was strong in both families, as indicated by high individual setting clonal repeatabilities ( e. g. Setting 3; outbred F-1 0.62 +/- 0.03 and inbred F-2 0.68 +/- 0.02 (H-2 +/- SE)) and the moderate-to-high genetic correlations amongst the three settings. For root biomass, clonal repeatabilities for both families were lower (outbred F-1 0.35 +/- 0.09 and inbred F-2 0.44 +/- 0.10 (H-2 +/- SE)). Weak positive genetic correlations between rooting percentage and root biomass in both families suggested a concomitant gain in root biomass would be insignificant when selecting solely on the more easily assessable rooting percentage.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

A hybrid planning method for transmission networks in a deregulated environment

The reconstruction of power industries has brought fundamental changes to both power system operation and planning. This paper presents a new planning method using multi-objective optimization (MOOP) technique, as well as human knowledge, to expand the transmission network in open access schemes. The method starts with a candidate pool of feasible expansion plans. Consequent selection of the best candidates is carried out through a MOOP approach, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in context of deregulated system. Human knowledge has been applied in both stages to ensure the selection with practical engineering and management concerns. The expansion plan from MOOP is assessed by reliability criteria before it is finalized. The proposed method has been tested with the IEEE 14-bus system and relevant analyses and discussions have been presented.

Evolution of the genetic covariance between male and female components of mate recognition: An experimental test

The evolution of a positive genetic correlation between male and female components of mate recognition systems will result as a consequence of assortative mating and, in particular, is central to a number of theories of sexual selection. Although the existence of such genetic correlations has been investigated in a number of taxa, it has yet to be shown that such correlations evolve and whether they may evolve as rapidly as suggested by sexual selection models. In this study, I used a hybridization experiment to disrupt natural mate recognition systems and then observed the subsequent evolutionary dynamics of the genetic correlation between male and female components for 56 generations in hybrids between Drosophila serrata and Drosophila birchii. The genetic correlation between male and female components evolved from 0.388 at generation 5 to 1.017 at generation 37 and then declined to -0.040 after a further 19 generations. These results indicated that the genetic basis of the mate recognition system in the hybrid populations evolved rapidly. The initial rapid increase in the genetic correlation was consistent with the classic assumption that male and female components will coevolve under sexual selection. The subsequent decline in genetic correlation may be attributable to the fixation of major genes or, alternatively, may be a result of a cyclic evolutionary change in mate recognition.

Genetic algorithms for continuous optimization problems - a concept of parameter-space size adjustment

The concept of parameter-space size adjustment is pn,posed in order to enable successful application of genetic algorithms to continuous optimization problems. Performance of genetic algorithms with six different combinations of selection and reproduction mechanisms, with and without parameter-space size adjustment, were severely tested on eleven multiminima test functions. An algorithm with the best performance was employed for the determination of the model parameters of the optical constants of Pt, Ni and Cr.

Combining the analyses of introgressive hybridisation and linkage mapping to investigate the genetic architecture of population divergence in the lake whitefish (Coregonus clupeaformis, Mitchill)

Adaptation and reproductive isolation, the engines of biological diversity, are still elusive when discussing the genetic bases of speciation. Namely, the number of genes and magnitude of selection acting positively or negatively on genomic traits implicated in speciation is contentious. Here, we describe the first steps of an ongoing research program aimed at understanding the genetic bases of population divergence and reproductive isolation in the lake whitefish (Coregonus clupeaformis). A preliminary linkage map originating from a hybrid cross between dwarf and normal ecotypes is presented, whereby some of the segregating AFLP markers were found to be conserved among natural populations. Maximum-likelihood was used to estimate hybrid indices from non-diagnostic markers at 998 AFLP loci. This allowed identification of the most likely candidate loci that have been under the influence of selection during the natural hybridisation of whitefish originating from different glacial races. As some of these loci could be identified on the linkage map, the possibility that selection of traits in natural populations may eventually be correlated to specific chromosomal regions was demonstrated. The future prospects and potential of these approaches to elucidate the genetic bases of adaptation and reproductive isolation among sympatric ecotypes of lake whitefish is discussed.

Spatial structure and habitat variation in a grasshopper hybrid zone

A hybrid zone between the grasshoppers Chorthippus brunneus and C. jacobsi (Orthoptera: Acrididae) in northern Spain has been analyzed for variation in morphology and ecology. These species are readily distinguished by the number of stridulatory pegs on the hind femur. Both sexes are fully winged and inhabit disturbed habitats throughout the study area. We develop a maximum-likelihood approach to fitting a two-dimensional cline to geographical variation in quantitative traits and for estimating associations of population mean with local habitat. This method reveals a cline in peg number approximately 30 km south of the Picos de Europa Mountains that shows substantial deviations in population mean compared with the expectations of simple tension zone models. The inclusion of variation in local vegetation in the model explains a significant proportion of the residual variation in peg number, indicating that habitat-genotype associations contribute to the observed spatial pattern. However, this association is weak, and a number of populations continue to show strong deviations in mean even after habitat is included in the final model. These outliers may be the result of long-distance colonization of sites distant from the cline center or may be due to a patchy pattern of initial contact during postglacial expansion. As well as contrasting with the smooth hybrid zones described for Chorthippus parallelus, this situation also contrasts with the mosaic hybrid zones observed in Gryllus crickets and in parts of the hybrid zone between Bombina toad species, where habitat-genotype associations account for substantial amounts of among-site variation.

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.