Comparative influence of forest management and habitat structural factors on the abundances of hollow-nesting bird species in subtropical Australian eucalypt forest

We examined the impact of single-tree selective logging and fuel reduction bums on the abundance of hollow-nesting bird species at a regional scale in southeastern Queensland, Australia. Data were collected on species abundance and habitat structure of dry sclerophyll production forest at 36 sites with known logging and fire histories. Sixteen bird species were recorded with most being resident, territorial, obligate hollow nesters that used hollows that were either small (18 cm diameter). Species densities were typically low, but combinations of two forest management and three habitat structural variables influenced the abundances of eight bird species in different and sometimes conflicting ways. The results suggest that habitat tree management for biodiversity in production forests cannot depend upon habitat structural characteristics alone. Management histories appear to have independent influence (on some bird species) that are distinguishable from their impacts on habitat structure per se. Rather than managing to maximize species abundances to maintain biodiversity, we may be better off managing to avoid extinctions of populations by identifying thresholds of acceptable fluctuations in populations of not only hollow-nesting birds but other forest dependent wildlife relative to scientifically valid forest management and habitat structural surrogates.

Peanut resistance to Sclerotinia minor and S-sclerotiorum

The fungi Sclerotinia minor and S. sclerotiorum are the causal agents of two similar diseases of peanut (Arachis hypogaea L.). Both diseases cause significant losses in the Australian peanut industry. Development of cultivars with resistance to Sclerotinia will be an important component of integrated control. The aims of this project are to generate information that will assist in breeding for Sclerotinia resistance in peanut: to identify Sclerotinia-resistant peanut germplasm, to understand the inheritance and estimate heritability of resistance, and to test the effectiveness of identified sources of resistance against both S. minor and S. sclerotiorum. This study has clearly established that material that shows resistance to S. minor in the USA is resistant to S. minor and likely to be resistant to S. sclerotiorum in Australia. The high level of resistance to both S. minor and S. sclerotiorum in germplasm from Texas, particularly TxAG-4, was confirmed. VA 93B showed good resistance in the field, which is primarily due to the open bush type rather than physiological resistance. Physiological resistance to S. minor was also identified in a cultivar and a landrace from Indonesia and a rust-resistant line from Queensland. All germplasm found to have high physiological resistance to S. minor belonged to the Spanish type. Inheritance of physiological resistance to S. minor was studied using a Generation Means Analysis (GMA) of the cross TxAG-4/VA 93B and its reciprocal. The broad-sense heritability of physiological resistance on a single plant basis was estimated at 47%, much higher than earlier estimates obtained in field studies. The average gene action of Sclerotinia resistance genes from TxAG-4 was found to be additive. No dominance effects were detected in the GMA. A small but significant reciprocal effect between TxAG-4 and VA 93B indicated that VA 93B passed on some physiological resistance maternally. An experiment was conducted to confirm the value of resistance against both S. minor and S. sclerotiorum. TxAG-4 was found to have physiological resistance to both S. minor and S. sclerotiorum. This resistance was expressed against both Sclerotinia species by progeny that were selected for resistance to S. minor. On the basis of the information obtained, the comparative advantages of 3 strategies for Sclerotinia-resistant cultivar development are discussed: (1) introduction of germplasm; (2) recurrent backcrossing with screening and crossing in the BCnF1 generation; and (3) pedigree selection. At present, introduction and backcrossing are recommended as the preferred strategies.

Differential sorting and fate of endocytosed GPI-anchored proteins

In this paper, we studied the fate of endocytosed glycosylphosphatidyl inositol anchored proteins (GPI-APs) in mammalian cells, using aerolysin, a bacterial toxin that binds to the GPI anchor, as a probe. We find that GPI-APs are transported down the endocytic pathway to reducing late endosomes in BHK cells, using biochemical, morphological and functional approaches. We also find that this transport correlates with the association to raft-like membranes and thus that lipid rafts are present in late endosomes (in addition to the Golgi and the plasma membrane). In marked contrast, endocytosed GPI-APs reach the recycling endosome in CHO cells and this transport correlates with a decreased raft association. GPI-APs are, however, diverted from the recycling endosome and routed to late endosomes in CHO cells, when their raft association is increased by clustering seven or less GPI-APs with an aerolysin mutant. We conclude that the different endocytic routes followed by GPI-APs in different cell types depend on the residence time of GPI-APs in lipid rafts, and hence that raft partitioning regulates GPI-APs sorting in the endocytic pathway.

Conditional simulation of random fields by successive residuals

This paper presents a new approach to the LU decomposition method for the simulation of stationary and ergodic random fields. The approach overcomes the size limitations of LU and is suitable for any size simulation. The proposed approach can facilitate fast updating of generated realizations with new data, when appropriate, without repeating the full simulation process. Based on a novel column partitioning of the L matrix, expressed in terms of successive conditional covariance matrices, the approach presented here demonstrates that LU simulation is equivalent to the successive solution of kriging residual estimates plus random terms. Consequently, it can be used for the LU decomposition of matrices of any size. The simulation approach is termed conditional simulation by successive residuals as at each step, a small set (group) of random variables is simulated with a LU decomposition of a matrix of updated conditional covariance of residuals. The simulated group is then used to estimate residuals without the need to solve large systems of equations.

Tillering in grain sorghum over a wide range of population densities: Identification of a common hierarchy for tiller emergence, leaf area development and fertility

Most studies of tiller development have not related the physiological and morphological features of each calm to its subsequent fertility. This introduced problems when trying to account for the effects of tillering on yield in crop models. The objective of this study was to detect the most likely early determinants of tiller fertility in sorghum by identifying hierarchies for emergence, fertility and grain number of tillers over a wide range of assimilate availabilities. Emergence, phenology, leaf area development and dry weight partitioning were quantified weekly for individual tillers and main culms of tillering and uniculm plants grown at one of four densities, from two to 16 plants m(-2). For a given plant in any given density, the same tiller hierarchy applied for emergence of tillers, fertility of the emerged tillers and their subsequent grain number. These results were observed over a range of tiller fertility rates (from 7 to 91%), fertile tiller number per plant at maturity (from 0.2 to 4.7), and tiller contribution to grain yield (from 5 to 78%). Tiller emergence was most probably related to assimilate supply and light quality. Development, fertility and contribution to yield of a specific tiller were highly dependent on growing conditions at the time of tiller emergence, particularly via early leaf area development of the tiller, which affected its subsequent leaf area accumulation. Assimilate availability in the main culm at the time of tiller emergence was the most likely early determinant of subsequent tiller fertility in this study. (C) 2002 Annals of Botany Company.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

Quantitative trait loci for agronomic and seed quality traits in an F-2 and F-4 : 6 soybean population

Molecular breeding is becoming more practical as better technology emerges. The use of molecular markers in plant breeding for indirect selection of important traits can favorably impact breeding efficiency. The purpose of this research is to identify quantitative trait loci (QTL) on molecular linkage groups (MLG) which are associated with seed protein concentration, seed oil concentration, seed size, plant height, lodging, and maturity, in a population from a cross between the soybean cultivars 'Essex' and 'Williams.' DNA was extracted from F-2 generation soybean leaves and amplified via polymerase chain reaction (PCR) using simple sequence repeat (SSR) markers. Markers that were polymorphic between the parents were analyzed against phenotypic trait data from the F-2 and F-4:6 generation. For the F-2 population, significant additive QTL were Satt540 (MLG M, maturity, r(2)=0.11; height, r(2)=0.04, seed size, r(2)=0.061, Satt373 (MLG L, seed size, r(2)=0.04; height, r(2)=0.14), Satt50 (MLG A1, maturity r(2)=0.07), Satt14 (MLG D2, oil, r(2)=0.05), and Satt251 (protein r(2)=0.03, oil, r(2)=0.04). Significant dominant QTL for the F-2 population were Satt540 (MLG M, height, r(2)=0.04; seed size, r(2)=0.06) and Satt14 (MLG D2, oil, r(2)=0.05). In the F-4:6 generation significant additive QTL were Satt239 (MLG I, height, r(2)=0.02 at Knoxville, TN and r(2)=0.03 at Springfield, TN), Satt14 (MLG D2, seed size, r(2)=0.14 at Knoxville, TN), Satt373 (MLG L, protein, r(2)=0.04 at Knoxville, TN) and Satt251 (MLG B I, lodging r(2)=0.04 at Springfield, TN). Averaged over both environments in the F-4:6 generation, significant additive QTL were identified as Satt251 (MLG B 1, protein, r(2)=0.03), and Satt239 (MLG 1, height, r(2)=0.03). The results found in this study indicate that selections based solely on these QTL would produce limited gains (based on low r(2) values). Few QTL were detected to be stable across environments. Further research to identify stable QTL over environments is needed to make marker-assisted approaches more widely adopted by soybean breeders.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

Special twin environments, genetic influences and their effects on the handedness of twins and their siblings

It has been suggested that twinning may influence handedness through the effects of birth order, intra-uterine crowding and mirror imaging. The influence of these effects on handedness (for writing and throwing) was examined in 3657 Monozygotic (MZ) and 3762 Dizygotic (DZ) twin pairs (born 1893-1992). Maximum likelihood analyses revealed no effects of birth order on the incidence of left-handedness. Twins were no more likely to be left-handed than their singleton siblings (n = 1757), and there were no differences between the DZ co-twin and sibling-twin covariances, suggesting that neither intra-uterine crowding nor the experience of being a twin affects handedness. There was no evidence of mirror imaging; the co-twin correlations of monochorionic and dichorionic MZ twins did not differ. Univariate genetic analyses revealed common environmental factors to be the most parsimonious explanation of familial aggregation for the writing-hand measure, while additive genetic influences provided a better interpretation of the throwing hand data.

The role of melanocortin-1 receptor polymorphism in skin cancer risk phenotypes

We have examined melanocortin-1 receptor (MC1R) variant allele frequencies in the general population and in a collection of adolescent dizygotic and monozygotic twins to determine statistical associations of pigmentation phenotypes with increased skin cancer risk. This included hair and skin color, freckling, mole count and sun exposed skin reflectance. Nine variants were studied and designated as either strong R (OR = 63; 95% CI 32-140) or weak r (OR = 5; 95% CI 3-11) red hair alleles. Penetrance of each MC1R variant allele was consistent with an allelic model where effects were multiplicative for red hair but additive for skin reflectance. To assess the interaction of the brown eye color gene BEY2/OCA2 on the phenotypic effects of variant MC1R alleles we imputed OCA2 genotype in the twin collection. A modifying effect of OCA2 on MC1R variant alleles was seen on constitutive skin color, freckling and mole count. In order to study the individual effects of these variants on pigmentation phenotype we have established a series of human primary melanocyte strains genotyped for the MC1R receptor. These include strains which are MC1R wild-type consensus, variant heterozygotes, and homozygotes for strong R alleles Arg151Cys and Arg160Trp. Ultrastructural analysis demonstrated that only consensus strains contained stage III and IV melanosomes in their terminal dendrites whereas Arg151Cys and Arg160Trp homozygous strains contained only immature stage I and II melanosomes. Such genetic association studies combined with the functional analysis of MC1R variant alleles in melanocytic cells should provide a link in understanding the association between pigmentary phototypes and skin cancer risk.

Genetic and Environmental Influences on Migraine: A Twin Study Across Six Countries

Migraine is a common neurovascular brain disorder that is manifested in recurrent episodes of disabling headache. The aim of the present study was to compare the prevalence and heritability of migraine across six of the countries that participate in GenomEutwin project including a total number of 29,717 twin pairs. Migraine was assessed by questionnaires that differed between most countries. It was most prevalent in Danish and Dutch females (32% and 34%, respectively), whereas the lowest prevalence was found in the younger and older Finnish cohorts (13% and 10%, respectively). The estimated genetic variance (heritability) was significant and the same between sexes in all countries. Heritability ranged from 34% to 57%, with lowest estimates in Australia, and highest estimates in the older cohort of Finland, the Netherlands, and Denmark. There was some indication that part of the genetic variance was non-additive, but this was significant in Sweden only. In addition to genetic factors, environmental effects that are non-shared between members of a twin pair contributed to the liability of migraine. After migraine definitions are homogenized among the participating countries, the GenomEUtwin project will provide a powerful resource to identify the genes involved in migraine.

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.

Sex differences in heritability of BMI: A comparative study of results from twin studies in eight countries

Body mass index (BMI), a simple anthropometric measure, is the most frequently used measure of adiposity and has been instrumental in documenting the worldwide increase in the prevalence of obesity witnessed during the last decades. Although this increase in overweight and obesity is thought to be mainly due to environmental changes, i.e., sedentary lifestyles and high caloric diets, consistent evidence from twin studies demonstrates high heritability and the importance of genetic differences for normal variation in BMI. We analysed self-reported data on BMI from approximately 37,000 complete twin pairs (including opposite sex pairs) aged 20-29 and 30-39 from eight different twin registries participating in the GenomEUtwin project. Quantitative genetic analyses were conducted and sex differences were explored. Variation in BMI was greater for women than for men, and in both sexes was primarily explained by additive genetic variance in all countries. Sex differences in the variance components were consistently significant. Results from analyses of opposite sex pairs also showed evidence of sex-specific genetic effects suggesting there may be some differences between men and women in the genetic factors that influence variation in BMI. These results encourage the continued search for genes of importance to the body composition and the development of obesity. Furthermore, they suggest that strategies to identify predisposing genes may benefit from taking into account potential sex specific effects.

Heritability of adult body height: A comparative study of twin cohorts in eight countries

A major component of variation in body height is due to genetic differences, but environmental factors have a substantial contributory effect. In this study we aimed to analyse whether the genetic architecture of body height varies between affluent western societies. We analysed twin data from eight countries comprising 30,111 complete twin pairs by using the univariate genetic model of the Mx statistical package. Body height and zygosity were self-reported in seven populations and measured directly in one population. We found that there was substantial variation in mean body height between countries; body height was least in Italy (177 cm in men and 163 cm in women) and greatest in the Netherlands (184 cm and 171 cm, respectively). In men there was no corresponding variation in heritability of body height, heritability estimates ranging from 0.87 to 0.93 in populations under an additive genes/unique environment (AE) model. Among women the heritability estimates were generally lower than among men with greater variation between countries, ranging from 0.68 to 0.84 when an additive genes/shared environment/unique environment (ACE) model was used. In four populations where an AE model fit equally well or better, heritability ranged from 0.89 to 0.93. This difference between the sexes was mainly due to the effect of the shared environmental component of variance, which appears to be more important among women than among men in our study populations. Our results indicate that, in general, there are only minor differences in the genetic architecture of height between affluent Caucasian populations, especially among men.

Direction of Causation Modeling Between Cross-Sectional Measures of Parenting and Psychological Distress in Female Twins

Under certain conditions, cross-sectional analysis of cross-twin intertrait correlations can provide important information about the direction of causation (DOC) between two variables. A community-based sample of Australian female twins aged 18 to 45 years was mailed an extensive Health and Lifestyle Questionnaire (HLQ) that covered a wide range of personality and behavioral measures. Included were self-report measures of recent psychological distress and perceived childhood environment (PBI). Factor analysis of the PBI yielded three interpretable dimensions: Coldness, Overprotection, and Autonomy. Univariate analysis revealed that parental Overprotection and Autonomy were best explained by additive genetic, shared, and nonshared environmental effects (ACE), whereas the best-fitting model for PBI Coldness and the three measures of psychological distress (Depression, Phobic Anxiety, and Somatic Distress) included only additive genetic and nonshared environmental effects (AE). A common pathway model best explained the covariation between (1) the three PBI dimensions and (2) the three measures of psychological distress. DOC modeling between latent constructs of parenting and psychological distress revealed that a model which specified recollected parental behavior as the cause of psychological distress provided a better fit than a model which specified psychological distress as the cause of recollected parental behavior. Power analyses and limitations of the findings are discussed.