How weed control and fertilisation influence tree physiological processes and growth at early establishment in an exotic F1 hybrid pine plantation of subtropical Australia

Purpose This study investigated how nitrogen (N) nutrition and key physiological processes varied under changed water and nitrogen competition resulting from different weed control and fertilisation treatments in a 2-year-old F1 hybrid (Pinus elliottii Engelm var. elliottii × P. caribaea var. hondurensis Barr. ex Golf.) plantation on a grey podzolic soil type, in Southeast Queensland. Materials and methods The study integrated a range of measures including growth variables (diameter at ground level (DGL), diameter at breast height (DBH) and height (H)), foliar variables (including foliar N concentration, foliar δ13C and δ15N) and physiological variables (including photosynthesis (An), stomatal conductance (gs), transpiration (E), intrinsic water use efficiency (WUEi) (A/gs) and xylem pressure potential (ΨXPP)) to better understand the mechanisms influencing growth under different weed control and fertilisation treatments. Five levels of weed control were applied: standard (routine), luxury, intermediate, mechanical and nil weed control, all with routine fertilisation plus an additional treatment, routine weed control and luxury fertilisation. Relative weed cover was assessed at 0.8, 1.1 and 1.6 years after plantation establishment to monitor the effectiveness of weed control treatments. Soil investigation included soil ammonium (NH4 +-N), nitrate (NO3 −-N), potentially mineralizable N (PMN), gravimetric soil moisture content (MC), hot water extractable organic carbon (HWETC), hot water extractable total N (HWETN), total C, total N, stable C isotope composition (δ13C), stable N isotope composition (δ15N), total P and extractable K. Results and discussion There were significant relationships between foliar N concentrations and relative weed cover and between tree growth and foliar N concentration or foliar δ15N, but initial site preparation practices also increased soil N transformations in the planting rows reducing the observable effects of weed control on foliar δ15N. A positive relationship between foliar N concentration and foliar δ13C or photosynthesis indicated that increased N availability to trees positively influenced non-stomatal limitations to photosynthesis. However, trees with increased foliar N concentrations and photosynthesis were negatively related to xylem pressure potential in the afternoons which enhanced stomatal limitations to photosynthesis and WUEi. Conclusions Luxury and intermediate weed control and luxury fertilisation positively influenced growth at early establishment by reducing the competition for water and N resources. This influenced fundamental key physiological processes such as the relationships between foliar N concentration, A n, E, gs and ΨXPP. Results also confirmed that time from cultivation is an important factor influencing the effectiveness of using foliar δ15N as an indicator of soil N transformations.

A note on the effective medium theory of random resistive-reactive medium

The effective medium theory for a system with randomly distributed point conductivity and polarisability is reformulated, with attention to cross-terms involving the two disorder parameters. The treatment reveals a certain inconsistency of the conventional theory owing to the neglect of the Maxwell-Wagner effect. The results are significant for the critical resistivity and dielectric anomalies of a binary liquid mixture at the phase separation point.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

Dilute Solution Properties of Methyl Methacrylate/Acrylonitrile Random Copolymers, 2a)

The Stockmayer-Fixman relation was used to evaluate the short range and long range interaction parameters for methyl methacrylate/acrylonitrile copolymers of 0,566 and 0,657 mole fraction of monomeric units of acrylonitrile in the solvents acetonitrile, 2-butanone, dimethyl formamide, and y-butyrolactone, at different temperatures (30, 45, and 60 “C). The values of KO were found to be lower than those of the parent homopolymers, and their values depend on both solvent and temperature. Even negative Ko-values were obtained, in cases in which the Mark Houwink exponent a is nearly unity. The values of the polymer-solvent interaction parameter, x, , are high and close to 0,5, indicating that these solvents are not good. The values of the excess interaction parameter, xAB, are negative and are not affected by temperature. The large extension of these copolymer chains, as exhibited by a and a;-values, can be understood in terms of unusual short range interactions only. Similar results were obtained for some cellulose derivatives.

Ecological processes and large-scale climate relationships in northern coniferous forests

Ilmasto vaikuttaa ekologisiin prosesseihin eri tasoilla. Suuren mittakaavan ilmastoprosessit, yhdessä ilmakehän ja valtamerien kanssa, säätelevät paikallisia sääilmiöitä suurilla alueilla (mantereista pallopuoliskoihin). Tämä väistöskirja pyrkii selittämään kuinka suuren mittakaavan ilmasto on vaikuttanut tiettyihin ekologisiin prosesseihin pohjoisella havumetsäalueella. Valitut prosessit olivat puiden vuosilustojen kasvu, metsäpalojen esiintyminen ja vuoristomäntykovakuoriaisen aiheuttamat puukuolemat. Suuren mittakaavan ilmaston löydettiin vaikuttaneen näiden prosessien esiintymistiheyteen, kestoon ja levinneisyyteen keskeisten sään muuttujien välityksellä hyvin laajoilla alueilla. Tutkituilla prosesseilla oli vahva yhteys laajan mittakaavan ilmastoon. Yhteys on kuitenkin ollut hyvin dynaaminen ja muuttunut 1900-luvulla ilmastonmuutoksen aiheuttaessa muutoksia suuren mittakaavan ja alueellisten ilmastoprosessien välisiin sisäisiin suhteisiin.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Integral Transformations of Volterra Gaussian Processes

We study integral representations of Gaussian processes with a pre-specified law in terms of other Gaussian processes. The dissertation consists of an introduction and of four research articles. In the introduction, we provide an overview about Volterra Gaussian processes in general, and fractional Brownian motion in particular. In the first article, we derive a finite interval integral transformation, which changes fractional Brownian motion with a given Hurst index into fractional Brownian motion with an other Hurst index. Based on this transformation, we construct a prelimit which formally converges to an analogous, infinite interval integral transformation. In the second article, we prove this convergence rigorously and show that the infinite interval transformation is a direct consequence of the finite interval transformation. In the third article, we consider general Volterra Gaussian processes. We derive measure-preserving transformations of these processes and their inherently related bridges. Also, as a related result, we obtain a Fourier-Laguerre series expansion for the first Wiener chaos of a Gaussian martingale. In the fourth article, we derive a class of ergodic transformations of self-similar Volterra Gaussian processes.

Understanding local processes: Contemplating franchisation

Increasing, there is growing acknowledgement of the importance of franchising within all modern global economies. Despite this, little is understood with regards the actual impact of franchising on local economies. This research aims to reframe the contribution of franchising by considering the process of franchisation. This study employed a mixed-method approach, utilizing critical realism to facilitate an outcomes-based explanation of firm survival. The focus of the study was upon generative mechanisms that were assumed to give rise to particular events from which (pizza) firm survival was enhanced vis-à-vis all other community members. A database of 2440 firms (or in excess of 21,000 company years) combined with archival records, interviews and the researcher’s observations provided the researcher with access to the nature of interaction occurring between firms. It was found that the survival of local firms was influenced positively by the day-to-day actions of franchise operators. However, it is argued that to understand how any such advantage my fall to local independent firms, we need too better appreciate the multitude of local processes related to such industries. This research re-examines several ecological concepts with the view of enabling a clearer investigation of underlying local processes. It also represents an authentic autecological approach to the study of firms.

On a generalized dynamic model of bi-state social interaction processes

A non-linear model, construed as a generalized version of the models put forth earlier for the study of bi-state social interaction processes, is proposed in this study. The feasibility of deriving the dynamics of such processes is demonstrated by establishing equivalence between the non-linear model and a higher order linear model.

Multi-state-choice automata model for expedient learning in random environment

A new automata model Mr,k, with a conceptually significant innovation in the form of multi-state alternatives at each instance, is proposed in this study. Computer simulations of the Mr,k, model in the context of feature selection in an unsupervised environment has demonstrated the superiority of the model over similar models without this multi-state-choice innovation.

Organizational competencies and dynamic Accounting Information System capability: Impact on AIS processes and firm performance

Accounting information systems (AIS) capture and process accounting data and provide valuable information for decision-makers. However, in a rapidly changing environment, continual management of the AIS is necessary for organizations to optimise performance outcomes. We suggest that building a dynamic AIS capability enables accounting process and organizational performance. Using the dynamic capabilities framework (Teece 2007) we propose that a dynamic AIS capability can be developed through the synergy of three competencies: a flexible AIS, having a complementary business intelligence system and accounting professionals with IT technical competency. Using survey data, we find evidence of a positive association between a dynamic AIS capability, accounting process performance, and overall firm performance. The results suggest that developing a dynamic AIS resource can add value to an organization. This study provides guidance for organizations looking to leverage the performance outcomes of their AIS environment.