Spatial population genetic structure reveals strong natal site fidelity in Echinocladius martini (Diptera: Chironomidae) in northeast Queensland, Australia

1. A diverse array of patterns has been reported regarding the spatial extent of population genetic structure and effective dispersal in freshwater macroinvertebrates. In river systems, the movements of many taxa can be restricted to varying degrees by the natural stream channel hierarchy. 2. In this study, we sampled populations of the non-biting freshwater midge Echinocladius martini in the Paluma bioregion of tropical northeast Queensland to investigate fine scale patterns of within- and among-stream dispersal and gene flow within a purported historical refuge. We amplified a 639 bp fragment of mitochondrial COI and analysed genetic structure using pairwise ΦST, hierarchical AMOVA, Mantel tests and a parsimony network. Genetic variation was partitioned among stream sections using Streamtree to investigate the effect of potential instream dispersal barriers. 3. The data revealed strong natal site fidelity and significant differentiation among neighbouring, geographically proximate streams. We found evidence for only episodic adult flight among sites on separate stream reaches. Overall, however, our data suggested that both larval and adult dispersal was largely limited to within a stream channel. 4. This may arise from a combination of the high density of riparian vegetation physically restricting dispersal and from the joint effects of habitat stability and large population sizes. Together these may mitigate the requirement for movement among streams to avoid inbreeding and local extinction due to habitat change and may thus enable persistence of upstream populations in the absence of regular compensatory upstream flight. Taken together, these data suggest that dispersal of E. martini is highly restricted, to the scale of only a few kilometres, and hence occurs predominantly within the natal stream.

Design of a preliminary error impact analysis model for spatial safety assessment of earthmoving operations

Regardless of technology benefits, safety planners still face difficulties explaining errors related to the use of different technologies and evaluating how the errors impact the performance of safety decision making. This paper presents a preliminary error impact analysis testbed to model object identification and tracking errors caused by image-based devices and algorithms and to analyze the impact of the errors for spatial safety assessment of earthmoving and surface mining activities. More specifically, this research designed a testbed to model workspaces for earthmoving operations, to simulate safety-related violations, and to apply different object identification and tracking errors on the data collected and processed for spatial safety assessment. Three different cases were analyzed based on actual earthmoving operations conducted at a limestone quarry. Using the testbed, the impacts of the errors were investigated for the safety planning purpose.

Investigation of stereotactic radiotherapy dose using dosimetry film and Monte Carlo simulations

This study uses dosimetry film measurements and Monte Carlo simulations to investigate the accuracy of type-a (pencil-beam) dose calculations for predicting the radiation doses delivered during stereotactic radiotherapy treatments of the brain. It is shown that when evaluating doses in a water phantom, the type-a algorithm provides dose predictions which are accurate to within clinically relevant criteria, gamma(3%,3mm), but these predictions are nonetheless subtly different from the results of evaluating doses from the same fields using radiochromic film and Monte Carlo simulations. An analysis of a clinical meningioma treatment suggests that when predicting stereotactic radiotherapy doses to the brain, the inaccuracies of the type-a algorithm can be exacerbated by inadequate evaluation of the effects of nearby bone or air, resulting in dose differences of up to 10% for individual fields. The results of this study indicate the possible advantage of using Monte Carlo calculations, as well as measurements with high-spatial resolution media, to verify type-a predictions of dose delivered in cranial treatments.

Framework for assessing financial literacy and superannuation investment choice decisions

There is a worldwide trend towards rapidly growing defined contribution pension funds in terms of assets and membership, and the choices available to individuals. This has shifted the decisionmaking responsibility to fund members for managing the investment of their retirement savings. This change has given rise to a phenomenon where most superannuation fund members are responsible for either actively choosing or passively relying on their funds’ default investment options. Prior research identifies that deficiencies in financial literacy is one of the causes of inertia in financial decision-making and findings from international and Australian studies show that financial illiteracy is wide-spread. Given the potential significant economic and social consequences of poor financial decision-making in superannuation matters, this paper proposes a framework by which the various demographic, social and contextual factors that influence fund members’ financial literacy and its association with investment choice decisions are explored. Enhanced theoretical and empirical understanding of the factors that are associated with active/passive investment choice decisions would enable development of well-targeted financial education programs.

Characteristics of utility cyclists in Queensland, Australia : an examination of the associations between individual, social and environmental factors and utility cycling

Background: Initiatives to promote utility cycling in countries like Australia and the US, which have low rates of utility cycling, may be more effective if they first target recreational cyclists. This study aimed to describe patterns of utility cycling and examine its correlates, among cyclists in Queensland, Australia. Methods: An online survey was administered to adult members of a state-based cycling community and advocacy group (n=1813). The survey asked about demographic characteristics and cycling behavior, motivators and constraints. Utility cycling patterns were described, and logistic regression modeling was used to examine associations between utility cycling and other variables. Results: Forty-seven percent of respondents reported utility cycling: most did so to commute (86%). Most journeys (83%) were >5 km. Being male, younger, employed full-time, or university-educated increased the likelihood of utility cycling (p<0.05). Perceiving cycling to be a cheap or a convenient form of transport were associated with utility cycling (p<0.05). Conclusions: The moderate rate of utility cycling among recreational cyclists highlights a potential to promote utility cycling among this group. To increase utility cycling, strategies should target female and older recreational cyclists and focus on making cycling a cheap and convenient mode of transport.

Sustainable assessment for large science classes : non-multiple choice, randomised assignments through a Learning Management System

This paper reports on the development of a tool that generates randomised, non-multiple choice assessment within the BlackBoard Learning Management System interface. An accepted weakness of multiple-choice assessment is that it cannot elicit learning outcomes from upper levels of Biggs’ SOLO taxonomy. However, written assessment items require extensive resources for marking, and are susceptible to copying as well as marking inconsistencies for large classes. This project developed an assessment tool which is valid, reliable and sustainable and that addresses the issues identified above. The tool provides each student with an assignment assessing the same learning outcomes, but containing different questions, with responses in the form of words or numbers. Practice questions are available, enabling students to obtain feedback on their approach before submitting their assignment. Thus, the tool incorporates automatic marking (essential for large classes), randomised tasks to each student (reducing copying), the capacity to give credit for working (feedback on the application of theory), and the capacity to target higher order learning outcomes by requiring students to derive their answers rather than choosing them. Results and feedback from students are presented, along with technical implementation details.

Probability distributed time delays: integrating spatial effects into temporal models

Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.