Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay

Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.

The Design, Implementation and Outcomes of a Mentoring Program

This paper reports on the design, implementation and outcomes of a mentoring program involving 18 employees in the IT Division of WorkCover Queensland. The paper provides some background information to the development of the program and the design and implementation phases including recruitment and matching of participants, orientation and training, and the mentoring process including transition and/or termination. The paper also outlines the quantitative and qualitative evaluation processes that occurred and the outcomes of that evaluation. Results indicated a wealth of positive individual, mentoring, and organisational outcomes. The organisation and semi-structured processes provided in the program are considered as major contributing factors to the successful outcomes of the program. These outcomes are likely to have long-term benefits for the individuals involved, the IT Division, and the broader organisation