Theoretical models suggest that in changing environments natural selection on two traits, maternal nesting behaviour and pivotal temperatures (those that divide the sexes) is important for maintaining viable offspring sex ratios in species with environmental sex determination (ESD). Empirical evidence, however, is lacking. In this paper, we provide such evidence from a study of clinal variation in four sex-determining traits (maternal nesting behaviour, pivotal temperatures, nesting phenology, and nest depth) in Physignathus lesueurii, a wide-ranging ESD lizard inhabiting eastern Australia. Despite marked differences in air and soil temperatures across our five study sites spanning 19°latitude and 1200 m in elevation, nest temperatures did not differ significantly among sites. Lizards compensated for climatic differences chiefly by selecting more open nest sites with higher incident radiation at cooler sites. Clinal variation in the onset of nesting also compensated for climatic differences, but to a lesser extent. There was no evidence of compensation through pivotal temperatures or nest depth. More broadly, our results extend to the egg stage the life history prediction that behaviour is the chief compensatory mechanism for climatic differences experienced by species spanning environmental extremes. Furthermore, our study was unique in revealing that nest site choice influenced mainly the daily range in nest temperatures, rather than mean temperatures, in a shallow-nesting reptile. Finally, indirect evidence suggests that the cue used by nesting lizards was radiation or temperature (through basking or assessing substrate temperatures), not visual detection of canopy openness. We conclude that maternal nesting behaviour and nesting phenology are traits subject to sex ratio selection in P. lesueurii, and thus, must be considered among the repertoire of ESD species for responding to climate change.

Leaf morphology and anatomy during vegetative phase change was compared in bluegrass, rice, and maize. Maize juvenile leaves are coated with epicuticular wax, lack specialized cells, such as trichomes and bulliform cells, and epidermal cell walls stain a uniform purple color. Adult maize leaves are pubescent, lack epicuticular waxes, and have crenulated epidermal cell walls that stain purple and blue. All bluegrass and rice blades are pubescent, coated with epicuticular waxes, and show purple and blue wall staining. In all three grasses, blade width steadily increases at each node until a threshold size is achieved several nodes before reproductive competence is acquired. Blade-to-sheath length showed a similar trend of continuous change followed by discontinuous change prior to reproduction. Analysis of leaf development demonstrated that maize primordia initiate more rapidly relative to blade and sheath growth than do either bluegrass or rice. We conclude that leaf shape, as defined by blade width and blade-to-sheath ratio, is a reliable indicator of phase, whereas anatomy is not a universal indicator of phase change in the grasses. We speculate that different growth patterns among these grasses may be attributed to changes in the timing of embryonic and postembryonic development.

Logistic, Gompertz, Richards and Weibull growth curves were evaluated for their suitability as mathematical and empirical models to represent cumulative germination. By avoiding the limitations associated with the method of moments and single-value germination indices, the fitted models provided superior description of the time course of germination. The four-parameter Weibull model gave the best fit across a relatively wide range of seed species and germination conditions, and the resulting parameter estimates reflected identifiable aspects of the germination process. The nonlinear estimation of the germination response included a parameter summary, together with their asymptotic standard errors and correlation matrix, along with an approximate band for the expectation function, pairwise plots of the parameter inference region, and profile t plots. Evaluation of the fitted models also included information on lack of fit and residual structure. Empirical results and hypothesis testing were demonstrated with reference to a replicated experiment designed to determine the effects of reduced water potential on germination of onion seeds.

AR-Mentor is a wearable real time Augmented Reality (AR) mentoring system that is configured to assist in maintenance and repair tasks of complex machinery, such as vehicles, appliances, and industrial machinery. The system combines a wearable Optical-See-Through (OST) display device with high precision 6-Degree-Of-Freedom (DOF) pose tracking and a virtual personal assistant (VPA) with natural language, verbal conversational interaction, providing guidance to the user in the form of visual, audio and locational cues. The system is designed to be heads-up and hands-free allowing the user to freely move about the maintenance or training environment and receive globally aligned and context aware visual and audio instructions (animations, symbolic icons, text, multimedia content, speech). The user can interact with the system, ask questions and get clarifications and specific guidance for the task at hand. A pilot application with AR-Mentor was successfully built to instruct a novice to perform an advanced 33-step maintenance task on a training vehicle. The initial live training tests demonstrate that AR-Mentor is able to help and serve as an assistant to an instructor, freeing him/her to cover more students and to focus on higher-order teaching.

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