A Bayesian Model of Pasture Curing

Curing percentage (the percentage of dead material in the sward) is a necessary component of fire behaviour modelling and subsequent fire danger ratings in grasslands. Current methods of estimating curing have limitations. Curing is controlled by leaf turnover in grasses but individual leaf turnover rates of themselves do not give estimates of curing. Bayesian modelling provides the potential to incorporate leaf turnover rates representing the entire life cycle of each leaf into a standalone model of curing from which statistical summaries can be generated and used in field models. In this study, curing percentage was estimated over thermal time for four common C3 grasses, and tested against field data

Leaf Growth and Senescence Rates in Brown-Back Wallaby Grass, \u3cem\u3eRytidosperma duttonianum\u3c/em\u3e

Knowledge of leaf turnover in grasses is necessary to model curing (the accumulation of dead material in the sward), which is not well represented in current pasture growth models, nor for many Australian native species. Leaf turnover begins with the appearance of successive leaves, which elongate until typically, a leaf ligule develops to indicate a mature, fully expanded length. Green leaf life span extends from appearance to the beginning of senescence, which ultimately leads to death (Fig. 1). Here, the individual rates of leaf growth and senescence for the Australian native brown-back wallaby grass, Rytidosperma duttonianum (Cashmore) Connor & Edgar, over the whole life cycle, are reported

A Plant-Physiology Approach to a Fire-y Problem

As vegetation dies, it dries and becomes more flammable. Fire agencies require accurate and timely assessments of curing (the percentage of dead material in the sward) to model grass fire behaviour and calculate fire danger ratings (Cheney and Sullivan 2008). Visual observation is commonplace and the more objective use of the Levy Rod is recommended, although both have drawbacks (Anderson et al. 2011). There is great potential for pasture growth models to provide curing estimates to assist with the management of wild grass fires (Gill et al. 2010). This PhD project focused on plant physiological characters to populate models that could be used to predict curing assessments for fire management purposes

Inferring the temperature dependence of population parameters: the effects of experimental design and inference algorithm

Understanding and quantifying the temperature dependence of population parameters, such as intrinsic growth rate and carrying capacity, is critical for predicting the ecological responses to environmental change. Many studies provide empirical estimates of such temperature dependencies, but a thorough investigation of the methods used to infer them has not been performed yet. We created artificial population time series using a stochastic logistic model parameterized with the Arrhenius equation, so that activation energy drives the temperature dependence of population parameters. We simulated different experimental designs and used different inference methods, varying the likelihood functions and other aspects of the parameter estimation methods. Finally, we applied the best performing inference methods to real data for the species Paramecium caudatum. The relative error of the estimates of activation energy varied between 5% and 30%. The fraction of habitat sampled played the most important role in determining the relative error; sampling at least 1% of the habitat kept it below 50%. We found that methods that simultaneously use all time series data (direct methods) and methods that estimate population parameters separately for each temperature (indirect methods) are complementary. Indirect methods provide a clearer insight into the shape of the functional form describing the temperature dependence of population parameters; direct methods enable a more accurate estimation of the parameters of such functional forms. Using both methods, we found that growth rate and carrying capacity of Paramecium caudatum scale with temperature according to different activation energies. Our study shows how careful choice of experimental design and inference methods can increase the accuracy of the inferred relationships between temperature and population parameters. The comparison of estimation methods provided here can increase the accuracy of model predictions, with important implications in understanding and predicting the effects of temperature on the dynamics of populations

Universality of Thermodynamic Constants Governing Biological Growth Rates

Background: Mathematical models exist that quantify the effect of temperature on poikilotherm growth rate. One family of such models assumes a single rate-limiting ‘master reaction ’ using terms describing the temperature-dependent denaturation of the reaction’s enzyme. We consider whether such a model can describe growth in each domain of life. Methodology/Principal Findings: A new model based on this assumption and using a hierarchical Bayesian approach fits simultaneously 95 data sets for temperature-related growth rates of diverse microorganisms from all three domains of life, Bacteria, Archaea and Eukarya. Remarkably, the model produces credible estimates of fundamental thermodynamic parameters describing protein thermal stability predicted over 20 years ago. Conclusions/Significance: The analysis lends support to the concept of universal thermodynamic limits to microbial growth rate dictated by protein thermal stability that in turn govern biological rates. This suggests that the thermal stability of proteins is a unifying property in the evolution and adaptation of life on earth. The fundamental nature of this conclusion has importance for many fields of study including microbiology, protein chemistry, thermal biology, and ecological theory including, for example, the influence of the vast microbial biomass and activity in the biosphere that is poorly described in current climate models

Variations in age- and sex-specific survival rates help explain population trend in a discrete marine mammal population

Funded by Department of Energy and Climate ChangePeer reviewedPublisher PD

Exploring the Use of Interactive Voice Response as a Population Health Tool

The research described in this thesis reviewed previous uses of Interactive Voice Response (IVR), developed appropriate software, and employed IVR to obtain self-report of sensitive issues in surveys and conduct brief public health interventions. Chapter 1 introduces IVR and describes a systematic critical review of the use of IVR. IVR is a telephone interviewing technique where the human speaker is replaced by a high quality recorded interactive script to which the respondent provides answers by pressing the keys of a touch-telephone (touchphone). IVR has numerous advantages, including: economy, autonomy, confidentiality, access to certain population groups, improved data quality, standardised interviewing, multi-lingual interfaces, and detailed longitudinal assessments. Despite this, there have been few survey applications of IVR compared to alternative methods such as Computer-Assisted Telephone Interview (CATI). There has not been any evaluation of the use of IVR for asking sensitive questions in surveys or as a tool for health promotion at the community level. A literature review, described in Chapter 2, was conducted to identify other methods of asking sensitive questions. The literature review identified 19 different methods. Those methods that were most successful were those that provided the greatest degree of anonymity to the respondent. It was suggested that IVR may be a suitable method for community surveys. As described in Chapter 3, a custom software called Generalized Electronic Interviewing System (GEIS) was developed. This provided both CATI and IVR interviewing modes. As described in Chapter 4, it was found that the response rate obtained using IVR was unacceptably low, and an alternative interviewing method, the Hybrid method was developed. In the Hybrid method the interview was initiated by the interviewer but completed using IVR with GEIS. As described in Chapter 5, the IVR, CATI and Hybrid methods were used to investigate self-reported rates of alcohol and drug consumption within a telephone household survey of 2880 households. The self-report rates were compared to the National Drug Strategy Household Survey (NDSHS). Response rates did not differ significantly between the CATI and Hybrid methods, however the response rate for IVR was significantly less than the other methods. The Hybrid and IVR methods obtained significantly higher self-report consumption rates for alcohol and marijuana, and significantly higher hazardous drinking scores using Alcohol Use Disorders Identification Test (AUDIT). In Chapter 6 a pilot of an IVR cervical screening brief advice interface is described. A total of 5000 households were contacted by the IVR system. The system randomly selected an eligible woman aged 18-69 per household and determined her cervical screening status. A total of 661 women listened to the IVR message. The IVR call was shown to be acceptable and inexpensive compared to a mail pamphlet intervention. In Chapter 7 a randomized controlled trial of an IVR cervical screening brief advice involving 17,008 households is described. Cervical screening rate data were obtained from the Health Insurance Commission (HIC) for a period spanning six months before and following the intervention. The cervical screening rate was increased in the intervention postcodes by 0.43% compared to the control postcodes, and the increase was greater for older women at 1.34%. This was a desirable outcome since this group is considered to be an at-risk group. The overall conclusion was that IVR technology could be feasibly used to contact women to deliver brief interventions aimed at increasing cervical screening rates, but the cost per screen was likely to be high. It is suggested that an IVR system could be linked to cervical screening registers to more directly and economically contact women, and provide an efficacious complementary approach to the existing letter reminder system.PhD Doctorat

A comparison of four computer-based telephone interviewing methods: getting answers to sensitive questions

Interactive voice response (IVR) technology presents a new and promising approach by which to collect accurate data on sensitive topics by telephone interviews. In a national survey of 2,880 households of alcohol and drug consumption, we compared computer-assisted telephone interviewing (CATI) and IVR with two hybrid methods that combine IVR with CATI. The principal hypothesis was that the selfreport rates of sensitive behaviors would be higher for the hybrid and IVR methods owing to greater perceived confidentiality than with CATI. All the methods obtained similar sample demographic compositions. Response rates did not differ significantly between the CATI and the hybrid methods; however, the response rate with IVR was significantly lower. The hybrid and IVR methods obtained significantly higher self-report consumption rates for alcohol and marijuana and significantly higher hazardous drinking scores, as measured by the Alcohol Use Disorders Identification Test (AUDIT)

Interactive voice response: review of studies 1989-2000

A systematic review of the use of interactive voice response (IVR) was conducted. IVR is a telephone interviewing technique in which the human speaker is replaced by a high-quality recorded interactive script to which the respondent provides answers by pressing the keys of a touch telephone (touchphone). IVR has numerous advantages, including economy, autonomy, confidentiality, access to certain population groups, improved data quality, standardized interviewing, multilingual interfaces, and detailed longitudinal assessments. Despite this, there have been few applications of IVR. Previous studies have been in the areas of information services, reminder calls, monitoring, assessment, experimentation, interventions, and surveys. Areas that have received little attention have been the systematic evaluation of voice, multilingual interfaces, touchphone prevalence, survey response rates, use by the elderly, and acceptability

Remote monitoring for wellbeing in grazing sheep: are social behaviours useful?

The increase in the use of electronic identification ear tags means that production traits specific to an individual sheep can be recorded and that presence, and possibly wellbeing, of individual sheep may be able to be monitored remotely. If data from monitoring systems is to be used to identify wellbeing status of individual sheep then behavioural measures recorded need to stable in a group of healthy individuals, have a short lag time and, where possible, reflect a variety of welfare and health issues. To date roll call, movement order and social networks have been assessed as potential measures of wellbeing. These measures are not ideal as identifiers of change in welfare state of grazing sheep as they do not meet the time frame or stability and repeatability requirements. Further work on a variety of other measures is underway using additional technologies such as temperature sensing microchips and video image analysis