Thermal requirements, field mortality and population phenology modelling of Paropsis atomaria Olivier, an emergent pest in subtropical hardwood plantations

Paropsis atomaria is a recently emerged pest of eucalypt plantations in subtropical Australia. Its broad host range of at least 20 eucalypt species and wide geographical distribution provides it the potential to become a serious forestry pest both within Australia and, if accidentally introduced, overseas. Although populations of P. atomaria are genetically similar throughout its range, population dynamics differ between regions. Here, we determine temperature-dependent developmental requirements using beetles sourced from temperate and subtropical zones by calculating lower temperature thresholds, temperature-induced mortality, and day-degree requirements. We combine these data with field mortality estimates of immature life stages to produce a cohort-based model, ParopSys, using DYMEX™ that accurately predicts the timing, duration, and relative abundance of life stages in the field and number of generations in a spring–autumn (September–May) field season. Voltinism was identified as a seasonally plastic trait dependent upon environmental conditions, with two generations observed and predicted in the Australian Capital Territory, and up to four in Queensland. Lower temperature thresholds for development ranged between 4 and 9 °C, and overall development rates did not differ according to beetle origin. Total immature development time (egg–adult) was approximately 769.2 ± S.E. 127.8 DD above a lower temperature threshold of 6.4 ± S.E. 2.6 °C. ParopSys provides a basic tool enabling forest managers to use the number of generations and seasonal fluctuations in abundance of damaging life stages to estimate the pest risk of P. atomaria prior to plantation establishment, and predict the occurrence and duration of damaging life stages in the field. Additionally, by using local climatic data the pest potential of P. atomaria can be estimated to predict the risk of it establishing if accidentally introduced overseas. Improvements to ParopSys’ capability and complexity can be made as more biological data become available.

Modeling videokeratoscopic height data with spherical harmonics

Purpose: All currently considered parametric models used for decomposing videokeratoscopy height data are viewercentered and hence describe what the operator sees rather than what the surface is. The purpose of this study was to ascertain the applicability of an object-centered representation to modeling of corneal surfaces. Methods: A three-dimensional surface decomposition into a series of spherical harmonics is considered and compared with the traditional Zernike polynomial expansion for a range of videokeratoscopic height data. Results: Spherical harmonic decomposition led to significantly better fits to corneal surfaces (in terms of the root mean square error values) than the corresponding Zernike polynomial expansions with the same number of coefficients, for all considered corneal surfaces, corneal diameters, and model orders. Conclusions: Spherical harmonic decomposition is a viable alternative to Zernike polynomial decomposition. It achieves better fits to videokeratoscopic height data and has the advantage of an object-centered representation that could be particularly suited to the analysis of multiple corneal measurements.

Realism and control : problem-based learning programs as a data source for work-related research

Problem-based learning (PBL) is a pedagogical methodology that presents the learner with a problem to be solved to stimulate and situate learning. This paper presents key characteristics of a problem-based learning environment that determines its suitability as a data source for workrelated research studies. To date, little has been written about the availability and validity of PBL environments as a data source and its suitability for work-related research. We describe problembased learning and use a research project case study to illustrate the challenges associated with industry work samples. We then describe the PBL course used in our research case study and use this example to illustrate the key attributes of problem-based learning environments and show how the chosen PBL environment met the work-related research requirements of the research case study. We propose that the more realistic the PBL work context and work group composition, the better the PBL environment as a data source for a work-related research. The work context is more realistic when relevant and complex project-based problems are tackled in industry-like work conditions over longer time frames. Work group composition is more realistic when participants with industry-level education and experience enact specialized roles in different disciplines within a professional community.

Nutrients build-up and wash-off processes in urban land uses

This thesis describes outcomes of a research study conducted to investigate the nutrient build-up and wash-off processes on urban impervious surfaces. The data needed for the study was generated through a series of field investigations and laboratory test procedures. The study sites were selected in urbanised catchments to represent typical characteristics of residential, industrial and commercial land uses. The build-up and wash-off samples were collected from road surfaces in the selected study sites. A specially designed vacuum collection system and a rainfall simulator were used for sample collection. According to the data analysis, the solids build-up on road surfaces was significantly finer with more than 80% of the particles below 150 ìm for all the land uses. Nutrients were mostly associated with the particle size range below 150 ìm in both build-up and wash-off samples irrespective of type of land use. Therefore, the finer fraction of solids was the most important for the nutrient build-up and particulate nutrient wash-off processes. Consequently, the design of stormwater quality mitigation measures should target particles less than 150 ìm for the removal of nutrients irrespective of type of land use. Total kjeldahl nitrogen (TKN) was the most dominant form of nitrogen species in build-up on road surfaces. Phosphorus build-up on road surfaces was mainly in inorganic form and phosphate (PO4 3-) was the most dominant form. The nutrient wash-off process was found to be dependent on rainfall intensity and duration. Concentration of both total nitrogen and phosphorus was higher at the beginning of the rain event and decreased with the increase in rainfall duration. Consequently, in the design of stormwater quality mitigation strategies for nutrients removal, it is important to target the initial period of rain events. The variability of wash-off of nitrogen with rainfall intensity was significantly different to phosphorus wash-off. The concentration of nitrogen was higher in the wash-off for low intensity rain events compared to the wash-off for high intensity rain events. On the other hand, the concentration of phosphorus in the wash-off was high for high intensity rain events compared to low intensity rain events. Consequently, the nitrogen washoff can be defined as a source limiting process and phosphorus wash-off as a transport limiting process. This highlights the importance of taking into consideration the wash-off of low intensity rain events in the design of stormwater quality mitigation strategies targeting the nitrogen removal. All the nitrogen species in wash-off are primarily in dissolved form whereas phosphorus is in particulate form. The differences in the nitrogen and phosphorus wash-off processes is principally due to the degree of solubility, attachment to particulates, composition of total nitrogen and total phosphorus and the degree of adherence of the solids particles to the surface to which nutrients are attached. The particulate nitrogen available for wash-off is removed readily as these are mobilised as free solids particles on the surface. Phosphorus is washed-off mostly with the solids particles which are strongly adhered to the surface or as the fixed solids load. Investigation of the nitrogen wash-off process using bulk wash-off samples was in close agreement with the investigation of dissolved fraction of wash-off solids. This was primarily due to the predominant nature of dissolved nitrogen. However, the investigation of the processes which underpin phosphorus wash-off using bulk washoff samples could lead to loss of information. This is due to the composition of total phosphorus in wash-off solids and the inherent variability of the wash-off process for the different particle size ranges. This variability should preferably be taken into consideration as phosphorus wash-off is predominantly in particulate form. Therefore, care needs to be taken in the investigation of the phosphorus wash-off process using bulk wash-off samples to ensure that there is no loss of information and hence result in misleading outcomes. The investigation of different particle size ranges of wash-off solids is preferable in the interest of designing effective stormwater quality management strategies targeting phosphorus removal.

Estimating interactive coefficients for analysing interactive failures

Engineering assets are often complex systems. In a complex system, components often have failure interactions which lead to interactive failures. A system with interactive failures may lead to an increased failure probability. Hence, one may have to take the interactive failures into account when designing and maintaining complex engineering systems. To address this issue, Sun et al have developed an analytical model for the interactive failures. In this model, the degree of interaction between two components is represented by interactive coefficients. To use this model for failure analysis, the related interactive coefficients must be estimated. However, methods for estimating the interactive coefficients have not been reported. To fill this gap, this paper presents five methods to estimate the interactive coefficients including probabilistic method; failure data based analysis method; laboratory experimental method; failure interaction mechanism based method; and expert estimation method. Examples are given to demonstrate the applications of the proposed methods. Comparisons among these methods are also presented.

Young children's early modelling with data

An educational priority of many nations is to enhance mathematical learning in early childhood. One area in need of special attention is that of statistics. This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling activities. Such modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (i.e., identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. Results are reported from the first year of a three-year longitudinal study in which three classes of first-grade children and their teachers engaged in activities that required the creation of data models. The theme of “Looking after our Environment,” a component of the children’s science curriculum at the time, provided the context for the activities. Findings focus on how the children dealt with given complex attributes and how they generated their own attributes in classifying broad data sets, and the nature of the models the children created in organising, structuring, and representing their data.