Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Occupational health nurses’ roles, credentials, and continuing education in Ontario, Canada

The role of the occupational health nurse is broad and includes health care provider, manager/coordinator, educator/advisor, and case manager and consultant, depending on the type of industry and the country in which the nurse practices. Regardless of the type of role, the occupational health nurse must participate in continuing nursing education (CNE) activities. This study describes the roles, credentials, and number of CNE activities undertaken by occupational health nurses working in Ontario, Canada. Using a non-experimental descriptive design, a questionnaire was mailed to all practicing occupational health nurses who are members (n = 900) of a local nursing association. Three hundred fifty-four questionnaires were returned. Nurses reported a variety of roles in the following categories: case management, health promotion, policy development, infection control/travel health, ergonomics, education, research, health and safety, direct care, consultation, disaster preparedness, and industrial hygiene. Sixty-five percent of nurses held an occupational health nurse credential, and 19% of nurses attended more than 100 hours of CNE annually. Occupational health nurses have multiple workplace roles. Many attend CNE activities and they often prepare for credentialing.

Massively parallel sequencing and analysis of expressed sequence tags in a successful invasive plant

Background Invasive species pose a significant threat to global economies, agriculture and biodiversity. Despite progress towards understanding the ecological factors associated with plant invasions, limited genomic resources have made it difficult to elucidate the evolutionary and genetic factors responsible for invasiveness. This study presents the first expressed sequence tag (EST) collection for Senecio madagascariensis, a globally invasive plant species. Methods We used pyrosequencing of one normalized and two subtractive libraries, derived from one native and one invasive population, to generate an EST collection. ESTs were assembled into contigs, annotated by BLAST comparison with the NCBI non-redundant protein database and assigned gene ontology (GO) terms from the Plant GO Slim ontologies. Key Results Assembly of the 221 746 sequence reads resulted in 12 442 contigs. Over 50 % (6183) of 12 442 contigs showed significant homology to proteins in the NCBI database, representing approx. 4800 independent transcripts. The molecular transducer GO term was significantly over-represented in the native (South African) subtractive library compared with the invasive (Australian) library. Based on NCBI BLAST hits and literature searches, 40 % of the molecular transducer genes identified in the South African subtractive library are likely to be involved in response to biotic stimuli, such as fungal, bacterial and viral pathogens. Conclusions This EST collection is the first representation of the S. madagascariensis transcriptome and provides an important resource for the discovery of candidate genes associated with plant invasiveness. The over-representation of molecular transducer genes associated with defence responses in the native subtractive library provides preliminary support for aspects of the enemy release and evolution of increased competitive ability hypotheses in this successful invasive. This study highlights the contribution of next-generation sequencing to better understanding the molecular mechanisms underlying ecological hypotheses that are important in successful plant invasions.

The Bayesian conditional independence model for measurement error: applications in ecology

The measurement error model is a well established statistical method for regression problems in medical sciences, although rarely used in ecological studies. While the situations in which it is appropriate may be less common in ecology, there are instances in which there may be benefits in its use for prediction and estimation of parameters of interest. We have chosen to explore this topic using a conditional independence model in a Bayesian framework using a Gibbs sampler, as this gives a great deal of flexibility, allowing us to analyse a number of different models without losing generality. Using simulations and two examples, we show how the conditional independence model can be used in ecology, and when it is appropriate.

Demonstration of cellulosic ethanol production from sugarcane bagasse in Australia : the Mackay Renewable Biocommodities Pilot Plant

The ready availability of sugarcane bagasse at an existing industrial facility and the potential availability of extra fibre through trash collection make sugarcane fibre the best candidate for early stage commercialisation of cellulosic ethanol technologies. The commercialisation of cellulosic ethanol technologies in the sugar industry requires both development of novel technologies and the assessment of these technologies at a pre-commercial scale. In 2007, the Queensland University of Technology (QUT) received funding from the Australian and Queensland Governments to construct a pilot research and development facility for the production of bioethanol and other renewable biocommodities from biomass including sugarcane bagasse. This facility has been built on the site of the Racecourse Sugar Mill in Mackay, Queensland and is known as the Mackay Renewable Biocommodities Pilot Plant (MRBPP). This research facility is capable of processing cellulosic biomass by a variety of pretreatment technologies and includes equipment for enzymatic saccharification, fermentation and distillation to produce ethanol. Lignin and fermentation co-products can also be produced in the pilot facility.