Predicting loss and fragmentation of habitat of the vulnerable subtropical rainforest tree Macadamia integrifolia with models developed from compiled ecological data

Habitat models are widely used in ecology, however there are relatively few studies of rare species, primarily because of a paucity of survey records and lack of robust means of assessing accuracy of modelled spatial predictions. We investigated the potential of compiled ecological data in developing habitat models for Macadamia integrifolia, a vulnerable mid-stratum tree endemic to lowland subtropical rainforests of southeast Queensland, Australia. We compared performance of two binomial models—Classification and Regression Trees (CART) and Generalised Additive Models (GAM)—with Maximum Entropy (MAXENT) models developed from (i) presence records and available absence data and (ii) developed using presence records and background data. The GAM model was the best performer across the range of evaluation measures employed, however all models were assessed as potentially useful for informing in situ conservation of M. integrifolia, A significant loss in the amount of M. integrifolia habitat has occurred (p < 0.05), with only 37% of former habitat (pre-clearing) remaining in 2003. Remnant patches are significantly smaller, have larger edge-to-area ratios and are more isolated from each other compared to pre-clearing configurations (p < 0.05). Whilst the network of suitable habitat patches is still largely intact, there are numerous smaller patches that are more isolated in the contemporary landscape compared with their connectedness before clearing. These results suggest that in situ conservation of M. integrifolia may be best achieved through a landscape approach that considers the relative contribution of small remnant habitat fragments to the species as a whole, as facilitating connectivity among the entire network of habitat patches.

Making use of pedagogic models as reflective catalysts for investigating pedagogic practice

The notion of pedagogy for anyone in the teaching profession is innocuous. The term itself, is steeped in history but the details of the practice can be elusive. What does it mean for an academic to be embracing pedagogy? The problem is not limited to academics; most teachers baulk at the introduction of a pedagogic agenda and resist attempts to have them reflect on their classroom teaching practice, where ever that classroom might be constituted. This paper explores the application of a pedagogic model (Education Queensland, 2001) which was developed in the context of primary and secondary teaching and was part of a schooling agenda to improve pedagogy. As a teacher educator I introduced the model to classroom teachers (Hill, 2002) using an Appreciative Inquiry (Cooperrider and Srivastva 1987) model and at the same time applied the model to my own pedagogy as an academic. Despite being instigated as a model for classroom teachers, I found through my own practitioner investigation that the model was useful for exploring my own pedagogy as a university academic (Hill, 2007, 2008). Cooperrider, D.L. and Srivastva, S. (1987) Appreciative inquiry in organisational life, in Passmore, W. and Woodman, R. (Eds) Research in Organisational Changes and Development (Vol 1) Greenwich, CT: JAI Press. Pp 129-69 Education Queensland (2001) School Reform Longitudinal Study (QSRLS), Brisbane, Queensland Government. Hill, G. (2002, December ) Reflecting on professional practice with a cracked mirror: Productive Pedagogy experiences. Australian Association for Research in Education Conference. Brisbane, Australia. Hill, G. (2007) Making the assessment criteria explicit through writing feedback: A pedagogical approach to developing academic writing. International Journal of Pedagogies and Learning 3(1), 59-66. Hill, G. (2008) Supervising Practice Based Research. Studies in Learning, Evaluation, Innovation and Development, 5(4), 78-87

An evaluation of IS-impact utility and intuitiveness

This study is conducted within the IS-Impact Research Track at Queensland University of Technology (QUT). The goal of the IS-Impact Track is, "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable et al, 2006). IS-Impact is defined as "a measure at a point in time, of the stream of net benefits from the IS [Information System], to date and anticipated, as perceived by all key-user-groups" (Gable Sedera and Chan, 2008). Track efforts have yielded the bicameral IS-Impact measurement model; the "impact" half includes Organizational-Impact and Individual-Impact dimensions; the "quality" half includes System-Quality and Information-Quality dimensions. The IS-Impact model, by design, is intended to be robust, simple and generalisable, to yield results that are comparable across time, stakeholders, different systems and system contexts. The model and measurement approach employs perceptual measures and an instrument that is relevant to key stakeholder groups, thereby enabling the combination or comparison of stakeholder perspectives. Such a validated and widely accepted IS-Impact measurement model has both academic and practical value. It facilitates systematic operationalisation of a main dependent variable in research (IS-Impact), which can also serve as an important independent variable. For IS management practice it provides a means to benchmark and track the performance of information systems in use. From examination of the literature, the study proposes that IS-Impact is an Analytic Theory. Gregor (2006) defines Analytic Theory simply as theory that ‘says what is’, base theory that is foundational to all other types of theory. The overarching research question thus is "Does IS-Impact positively manifest the attributes of Analytic Theory?" In order to address this question, we must first answer the question "What are the attributes of Analytic Theory?" The study identifies the main attributes of analytic theory as: (1) Completeness, (2) Mutual Exclusivity, (3) Parsimony, (4) Appropriate Hierarchy, (5) Utility, and (6) Intuitiveness. The value of empirical research in Information Systems is often assessed along the two main dimensions - rigor and relevance. Those Analytic Theory attributes associated with the ‘rigor’ of the IS-Impact model; namely, completeness, mutual exclusivity, parsimony and appropriate hierarchy, have been addressed in prior research (e.g. Gable et al, 2008). Though common tests of rigor are widely accepted and relatively uniformly applied (particularly in relation to positivist, quantitative research), attention to relevance has seldom been given the same systematic attention. This study assumes a mainly practice perspective, and emphasises the methodical evaluation of the Analytic Theory ‘relevance’ attributes represented by the Utility and Intuitiveness of the IS-Impact model. Thus, related research questions are: "Is the IS-Impact model intuitive to practitioners?" and "Is the IS-Impact model useful to practitioners?" March and Smith (1995), identify four outputs of Design Science: constructs, models, methods and instantiations (Design Science research may involve one or more of these). IS-Impact can be viewed as a design science model, composed of Design Science constructs (the four IS-Impact dimensions and the two model halves), and instantiations in the form of management information (IS-Impact data organised and presented for management decision making). In addition to methodically evaluating the Utility and Intuitiveness of the IS-Impact model and its constituent constructs, the study aims to also evaluate the derived management information. Thus, further research questions are: "Is the IS-Impact derived management information intuitive to practitioners?" and "Is the IS-Impact derived management information useful to practitioners? The study employs a longitudinal design entailing three surveys over 4 years (the 1st involving secondary data) of the Oracle-Financials application at QUT, interspersed with focus groups involving senior financial managers. The study too entails a survey of Financials at four other Australian Universities. The three focus groups respectively emphasise: (1) the IS-Impact model, (2) the 2nd survey at QUT (descriptive), and (3) comparison across surveys within QUT, and between QUT and the group of Universities. Aligned with the track goal of producing IS-Impact scores that are highly comparable, the study also addresses the more specific utility-related questions, "Is IS-Impact derived management information a useful comparator across time?" and "Is IS-Impact derived management information a useful comparator across universities?" The main contribution of the study is evidence of the utility and intuitiveness of IS-Impact to practice, thereby further substantiating the practical value of the IS-Impact approach; and also thereby motivating continuing and further research on the validity of IS-Impact, and research employing the ISImpact constructs in descriptive, predictive and explanatory studies. The study also has value methodologically as an example of relatively rigorous attention to relevance. A further key contribution is the clarification and instantiation of the full set of analytic theory attributes.

Hierarchical models for 2D presence/absence data having ambiguous zeroes: With a biogeographical case study on dingo behaviour

This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.

Development and validation of a novel approach to work sampling : a study of nurse practitioner work patterns

Objectives: This methodological paper reports on the development and validation of a work sampling instrument and data collection processes to conduct a national study of nurse practitioners’ work patterns. ---------- Design: Published work sampling instruments provided the basis for development and validation of a tool for use in a national study of nurse practitioner work activities across diverse contextual and clinical service models. Steps taken in the approach included design of a nurse practitioner-specific data collection tool and development of an innovative web-based program to train and establish inter rater reliability of a team of data collectors who were geographically dispersed across metropolitan, rural and remote health care settings. ---------- Setting: The study is part of a large funded study into nurse practitioner service. The Australian Nurse Practitioner Study is a national study phased over three years and was designed to provide essential information for Australian health service planners, regulators and consumer groups on the profile, process and outcome of nurse practitioner service. ---------- Results: The outcome if this phase of the study is empirically tested instruments, process and training materials for use in an international context by investigators interested in conducting a national study of nurse practitioner work practices. ---------- Conclusion: Development and preparation of a new approach to describing nurse practitioner practices using work sampling methods provides the groundwork for international collaboration in evaluation of nurse practitioner service.

Soil carbon saturation : concept, evidence and evaluation

Current estimates of soil C storage potential are based on models or factors that assume linearity between C input levels and C stocks at steady-state, implying that SOC stocks could increase without limit as C input levels increase. However, some soils show little or no increase in steady-state SOC stock with increasing C input levels suggesting that SOC can become saturated with respect to C input. We used long-term field experiment data to assess alternative hypotheses of soil carbon storage by three simple models: a linear model (no saturation), a one-pool whole-soil C saturation model, and a two-pool mixed model with C saturation of a single C pool, but not the whole soil. The one-pool C saturation model best fit the combined data from 14 sites, four individual sites were best-fit with the linear model, and no sites were best fit by the mixed model. These results indicate that existing agricultural field experiments generally have too small a range in C input levels to show saturation behavior, and verify the accepted linear relationship between soil C and C input used to model SOM dynamics. However, all sites combined and the site with the widest range in C input levels were best fit with the C-saturation model. Nevertheless, the same site produced distinct effective stabilization capacity curves rather than an absolute C saturation level. We conclude that the saturation of soil C does occur and therefore the greatest efficiency in soil C sequestration will be in soils further from C saturation.

In vivo evaluation of an ultra-thin polycaprolactone film as a wound dressing

The use of ultra-thin films as dressings for cutaneous wounds could prove advantageous in terms of better conformity to wound topography and improved vapour transmission. For this purpose, ultra-thin poly(epsilon-caprolactone) (PCL) films of 5-15 microm thickness were fabricated via a biaxial stretching technique. To evaluate their in vivo biocompatibility and feasibility as an external wound dressing, PCL films were applied over full and partial-thickness wounds in rat and pig models. Different groups of PCL films were used: untreated, NaOH-treated, untreated with fibrin, NaOH-treated with perforations, and NaOH-treated with fibrin and S-nitrosoglutathione. Wounds with no external dressings were used as controls. Wound contraction rate, histology and biomechanical analyses were carried out. Wounds re-epithelialized completely at a comparable rate. Formation of a neo-dermal layer and re-epithelialization were observed in all the wounds. A lower level of fibrosis was observed when PCL films were used, compared to the control wounds. Ultimate tensile strength of the regenerated tissue in rats reached 50-60% of that in native rat skin. Results indicated that biaxially-stretched PCL films did not induce inflammatory reactions when used in vivo as a wound dressing and supported the normal wound healing process in full and partial-thickness wounds.

Sustainability performance of construction : conceptual models of satisfaction levels in construction projects

In general, the performance of construction projects, including their sustainability performance, does not meet optimal expectations. One aspect of this is the performance of the participants who are independent and make a significance impact on overall project outcomes. Of these participants, the client is traditionally the owner of the project, the architect or engineer is engaged as the lead designer and a contractor is selected to construct the facilities. Generally, the performance of the participants is gauged by considering three main factors, namely, time, cost and quality. As the level of satisfaction is a subjective issue, it is rarely used in the performance evaluation of construction work. Recently, various approaches to the measurement of satisfaction have been made in an attempt to determine the performance of construction project outcomes - for instance, client satisfaction, customer satisfaction, contractor satisfaction, occupant satisfaction and home buyer satisfaction. These not only identify the performance of the construction project but are also used to improve and maintain relationships. In addition, these assessments are necessary for the continuous improvement and enhanced cooperation of participants. The measurement of satisfaction levels primarily involves expectations and perceptions. An expectation can be regarded as a comparative standard of different needs, motives and beliefs, while a perception is a subjective interpretation that is influenced by moods, experiences and values. This suggests that the disparity between perceptions and expectations may possibly be used to represent different levels of satisfaction. However, this concept is rather new and in need of further investigation. This chapter examines the methods commonly practised in measuring satisfaction levels today and the advantages of promoting these methods. The results provide a preliminary review of the advantages of satisfaction measurement in the construction industry and recommendations are made concerning the most appropriate methods to use in identifying the performance of project outcomes.

The use of economic evaluation in CAM : an introductory framework

Background For CAM to feature prominently in health care decision-making there is a need to expand the evidence-base and to further incorporate economic evaluation into research priorities. In a world of scarce health care resources and an emphasis on efficiency and clinical efficacy, CAM, as indeed do all other treatments, requires rigorous evaluation to be considered in budget decision-making. Methods Economic evaluation provides the tools to measure the costs and health consequences of CAM interventions and thereby inform decision making. This article offers CAM researchers an introductory framework for understanding, undertaking and disseminating economic evaluation. The types of economic evaluation available for the study of CAM are discussed, and decision modelling is introduced as a method for economic evaluation with much potential for use in CAM. Two types of decision models are introduced, decision trees and Markov models, along with a worked example of how each method is used to examine costs and health consequences. This is followed by a discussion of how this information is used by decision makers. Conclusions Undoubtedly, economic evaluation methods form an important part of health care decision making. Without formal training it can seem a daunting task to consider economic evaluation, however, multidisciplinary teams provide an opportunity for health economists, CAM practitioners and other interested researchers, to work together to further develop the economic evaluation of CAM.

Conceptual models of satisfaction level in construction

It is recognized that, in general, the performance of construction projects does not meet optimal expectations. One aspect of this is the performance of each participant, which is interdependent and makes a significance impact on overall project outcomes. Of these, the client is traditionally the owner of the project, the architect or engineer is engaged as the lead designer and a contractor is selected to construct the facilities. Generally, the performance of the participants is gauged by considering three main factors, namely time, cost and quality. As the level of satisfaction is a subjective measurement, it is rarely used in the performance evaluation of construction work. Recently, various approaches to the measurement of satisfaction have been made in attempting to determine the performance of construction project outcomes – for instance client satisfaction, consultant satisfaction, contractor satisfaction, customer satisfaction and home buyer satisfaction. These not only identify the performance of the construction project, but are also used to improve and maintain relationships. In addition, these assessments are necessary for continuous improvement and enhanced cooperation between participants. The measurement of satisfaction levels primarily involves expectations and perceptions. An expectation can be regarded as a comparison standard of different needs, motives and beliefs, while a perception is a subjective interpretation that is influenced by moods, experiences and values. This suggests that the disparity between perceptions and expectations may be used to represent different levels of satisfaction. However, this concept is rather new and in need of further investigation. This paper examines the current methods commonly practiced in measuring satisfaction level and the advantages of promoting these methods. The results provided are a preliminary review of the advantages of satisfaction measurement in the construction industry and recommendations are made concerning the most appropriate methods for use in identifying the performance of project outcomes.

Expertise in software design : novice and expert models

This paper investigates how software designers use their knowledge during the design process. The research is based on the analysis of the observational and verbal data from three software design teams generated during the conceptual stage of the design process. The knowledge captured from the analysis of the mapped design team data is utilized to generate descriptive models of novice and expert designers. These models contribute to a better understanding of the connections between, and integration of, designer variables, and to a better understanding of software design expertise and its development. The models are transferable to other domains.

In vivo performance of melimine as an antimicrobial coating for contact lenses in models of CLARE and CLPU

Purpose: One strategy to minimize bacteria-associated adverse responses such as microbial keratitis, contact lens–induced acute red eye (CLARE), and contact lens induced peripheral ulcers (CLPUs) that occur with contact lens wear is the development of an antimicrobial or antiadhesive contact lens. Cationic peptides represent a novel approach for the development of antimicrobial lenses.---------- Methods: A novel cationic peptide, melimine, was covalently incorporated into silicone hydrogel lenses. Confirmation tests to determine the presence of peptide and anti-microbial activity were performed. Cationic lenses were then tested for their ability to prevent CLPU in the Staphylococcus aureus rabbit model and CLARE in the Pseudomonas aeruginosa guinea pig model. ---------- Results: In the rabbit model of CLPU, melimine-coated lenses resulted in significant reductions in ocular symptom scores and in the extent of corneal infiltration (P < 0.05). Evaluation of the performance of melimine lenses in the CLARE model showed significant improvement in all ocular response parameters measured, including the percentage of eyes with corneal infiltrates, compared with those observed in the eyes fitted with the control lens (P ≤ 0.05). ---------- Conclusions: Cationic coating of contact lenses with the peptide melimine may represent a novel method of prevention of bacterial growth on contact lenses and consequently result in reduction of the incidence and severity of adverse responses due to Gram-positive and -negative bacteria during lens wear.

Discovering characteristics of stochastic collections of process models

Process models in organizational collections are typically modeled by the same team and using the same conventions. As such, these models share many characteristic features like size range, type and frequency of errors. In most cases merely small samples of these collections are available due to e.g. the sensitive information they contain. Because of their sizes, these samples may not provide an accurate representation of the characteristics of the originating collection. This paper deals with the problem of constructing collections of process models, in the form of Petri nets, from small samples of a collection for accurate estimations of the characteristics of this collection. Given a small sample of process models drawn from a real-life collection, we mine a set of generation parameters that we use to generate arbitrary-large collections that feature the same characteristics of the original collection. In this way we can estimate the characteristics of the original collection on the generated collections.We extensively evaluate the quality of our technique on various sample datasets drawn from both research and industry.