Owen Woodberry

Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment

Catchment managers face considerable challenges in managing ecological assets. This task is made difficult by the variable and complex nature of ecological assets, and the considerable uncertainty involved in quantifying how various threats and hazards impact upon them. Bayesian approaches have the potential to address the modelling needs of environmental management. However, to date many Bayesian networks (Bn) developed for environmental management have been parameterised using knowledge elicitation only. Not only are these models highly qualitative, but the time and effort involved in elicitation of a complex Bn can often be overwhelming. Unfortunately in environmental applications, data alone are often too limited for parameterising a Bn. Consequently, there is growing interest in how to parameterise Bns using both data and elicited information. At present, there is little formal guidance on how to combine what can be learned from the data with what can be elicited. In a previous publication we proposed a detailed methodology for this process, focussing on parameterising and evaluating a Bn. In this paper, we further develop this methodology using a risk assessment case study, with the focus being on native fish communities in the Goulburn Catchment (Victoria, Australia).

Parameterising bayesian networks

Most documented Bayesian network (BN) applications have been built through knowledge elicitation from domain experts (DEs) The difficulties involved have led to growing interest in machine learning of BNs from data There is a further need for combining what can be learned from the data with what can be elicited from DEs In this paper, we propose a detailed methodology for this combination, specifically for the parameters of a BN.

Testing Punctuated Equilibrium Theory Using Evolutionary Activity Statistics

The Punctuated Equilibrium hypothesis (Eldredge and Gould,1972) asserts that most evolutionary change occurs during geologically rapid speciation events, with species exhibiting stasis most of the time. Punctuated Equilibrium is a natural extension of Mayrs theories on peripatric speciation via the founder effect, (Mayr, 1963; Eldredge and Gould, 1972) which associates changes in diversity to a population bottleneck. That is, while the formation of a foundation bottleneck brings an initial loss of genetic variation, it may subsequently result in the emergence of a child species distinctly different from its parent species. In this paper we adapt Bedaus evolutionary activity statistics (Bedau and Packard, 1991) to test these effects in an ALife simulation of speciation. We find a relative increase in evolutionary activity during speciations events, indicating that punctuation is occurring.

Predicting island biosecurity risk from introduced fauna using Bayesian Belief Networks

Around the globe, islands are the last refuge for many threatened and endemic species. Islands are frequently also important sites for recreation, cultural activities, and industrial development, all of which facilitate the establishment of invasive species. Surveillance is employed on islands to detect the establishment of invasive species after their arrival, leading to decisions about follow-up actions. Unless surveillance is prioritised according to risk of establishment of invasives, it may be infeasible to implement efficiently over large tracts of publicly accessible land, especially in data-deficient areas. The key biosecurity problem for many regions is one of prioritizing sites for surveillance activities and identifying invasive species most likely to disperse to, and establish, and proliferate on those sites. We created a series of Bayesian Belief Networks (BBNs), linked by Java computing code and the freely available GeNIe application to automate the creation and computation of species- and site-specific biosecurity BBNs. The BBNs require data on island attributes, recreational or industrial visitor load, infrastructure, habitat availability, and animal behaviour and dispersal via swimming, flying, human movement, land bridges, or flood plumes. We used this biosecurity BBN to estimate the risk of 11 invasive faunal species arriving and establishing on 600 islands along the Pilbara coastline, Western Australia. Sensitivity analyses were conducted to identify nodes within the BBNs that required refined data inputs. Propagule pressure was the node with the greatest influence over the number of arrivals. Other nodes such as the number of visitors to islands and swimming capabilities of invasive animals greatly influenced the model results. Across the 11 species studied, our models predicted one arrival per 300 visitors. The biosecurity BBN can be used to identify the islands at highest risk from establishment of invasive species within any archipelago/s, and the invasive species most likely to establish on each island.