Info-gap theory to determine cost-effective eradication of invasive species.

Invasive species eradication campaigns often fail due to stochastic arrival events, unpredictable detectability and incorrect resource allocation. Severe uncertainty in model parameter estimates may skew the eradication policy results. Using info-gap decision theory, this research aims to provide managers with a method to quantify their confidence in realizing successful eradication of particular invasive species within their specified eradication budgets (i.e. allowed eradication cost) in face of information-gaps. The potential introduction of the Asian house gecko Hemidactylus frenatus to Barrow Island, Australia is used as a case study to illustrate the model. Results of this research demonstrate that, more robustness to uncertainty in the model parameters can be earnt by (1) increasing the allowed eradication cost (2) investment in pre-border quarantine and border inspection (i.e. prevention) or (3) investment in post-border detection surveillance. The combination of a post-border spatial dispersal model and info-gap decision theory demonstrates a novel and spatially efficient method for managers to evaluate the robustness of eradication policies for incursion of invasive species with unexpected behaviour. These methods can be used to provide insight into the success of management goals, in particular the eradication of invasive species on islands or in broader mainland areas. These insights will assist in avoiding eradication failure and wasteful budget allocation and labour investment.

Evaluation of the Likelihood of Establishing False Codling Moth (Thaumatotibia leucotreta) in Australia via the International Cut Flower Market.

Kenya and some other African countries are threatened by a serious pest Thaumatotibia leucotreta (Meyrick) (Lepidoptera: Tortricidae), the false codling moth. The detection of T. leucotreta is quite difficult due to the cryptic nature of the larvae during transportation and is therefore a concern for Australia. This insect is a known pest of agriculturally important crops. Here, Maxent was used to assess the biosecurity threat of T. leucotreta to Australia. Habitat suitability and risk assessment of T. leucotreta in Australia were identified based on threatened areas under suitable climatic conditions and the presence of hosts in a given habitat. Modeling indicated that Australia is vulnerable to invasion and establishment by T. leucotreta in some states and territories, particularly areas of western and southern Australia. Within these locations, the risk is associated with specific cropping areas. As such, invasion and establishment by T. leucotreta may have serious implications for Australia's agricultural and horticultural industries e.g., the fruit and vegetable industries. This study will be used to inform the government and industry of the threat posed by T. leucotreta imported via the cut flower industry. Targeted preventative measures and trade policy could be introduced to protect Australia from invasion by this pest.

Use of mixed-type data clustering algorithm for characterizing temporal and spatial distribution of biosecurity border detections of terrestrial non-indigenous species.

Appropriate inspection protocols and mitigation strategies are a critical component of effective biosecurity measures, enabling implementation of sound management decisions. Statistical models to analyze biosecurity surveillance data are integral to this decision-making process. Our research focuses on analyzing border interception biosecurity data collected from a Class A Nature Reserve, Barrow Island, in Western Australia and the associated covariates describing both spatial and temporal interception patterns. A clustering analysis approach was adopted using a generalization of the popular k-means algorithm appropriate for mixed-type data. The analysis approach compared the efficiency of clustering using only the numerical data, then subsequently including covariates to the clustering. Based on numerical data only, three clusters gave an acceptable fit and provided information about the underlying data characteristics. Incorporation of covariates into the model suggested four distinct clusters dominated by physical location and type of detection. Clustering increases interpretability of complex models and is useful in data mining to highlight patterns to describe underlying processes in biosecurity and other research areas. Availability of more relevant data would greatly improve the model. Based on outcomes from our research we recommend broader use of cluster models in biosecurity data, with testing of these models on more datasets to validate the model choice and identify important explanatory variables.

Biosecurity risks posed by a large sea-going passenger vessel: challenges of terrestrial arthropod species detection and eradication.

Large sea-going passenger vessels can pose a high biosecurity risk. The risk posed by marine species is well documented, but rarely the risk posed by terrestrial arthropods. We conducted the longest running, most extensive monitoring program of terrestrial arthropods undertaken on board a passenger vessel. Surveillance was conducted over a 19-month period on a large passenger (cruise) vessel that originated in the Baltic Sea (Estonia). The vessel was used as an accommodation facility to house workers at Barrow Island (Australia) for 15 months, during which 73,061 terrestrial arthropods (222 species - four non-indigenous (NIS) to Australia) were collected and identified on board. Detection of Tribolium destructor Uytt., a high-risk NIS to Australia, triggered an eradication effort on the vessel. This effort totalled more than 13,700 human hours and included strict biosecurity protocols to ensure that this and other non-indigenous species (NIS) were not spread from the vessel to Barrow Island or mainland Australia. Our data demonstrate that despite the difficulties of biosecurity on large vessels, stringent protocols can stop NIS spreading from vessels, even where vessel-wide eradication is not possible. We highlight the difficulties associated with detecting and eradicating NIS on large vessels and provide the first detailed list of species that inhabit a vessel of this kind.

Commercial trials evaluating the novel use of ethyl formate for in-transit fumigation of shipping containers.

The use of shipping containers for cargo transportation has the potential to transport insect pests from infested to non-infested areas. Therefore, fumigation is required as an appropriate biosecurity measure to exterminate these pests. In-transit fumigation trials were conducted in two 20 ft shipping containers during a two-day journey in both September and December 2017. Ethyl formate (90 g m-3) was purged with nitrogen (EF + N2) into the containers. Ethyl formate concentration inside containers and the surrounding environment were monitored at timed intervals throughout the journey. Fumigation achieved sufficient concentration × time (Ct) products in the containers during the journey, which can exterminate all stages of most common insect pests. The Ct products in-transit were greater than those in a shipping container being fumigated in a stationary position at a dose rate of 90 g m-³ for 24 hours exposure. Levels of EF in the environment between 1-15 m downwind from the containers and driver's cabin were less than 0.5 ppm at each of the timed intervals, 200 times below 100 ppm of EF Threshold Limit Value (TLV). Our study indicates that in-transit EF + N2 technology has the potential to deliver cost savings in the fumigation process through reduction of the Labor cost, elimination of the time a container and cargo must remain stationary in a fumigation yard and a significant decrease in total supply chain time (between container packing and receival).

Underwater video as a monitoring tool to detect change in seagrass cover.

To date seagrass monitoring has involved the removal of seagrass from its environment. In fragile or highly disturbed systems, monitoring using destructive techniques may interfere with the environment or add to the burden of disturbance. Video photography is a form of non-destructive monitoring that does not require the removal of seagrass or interference with the environment and has the potential to be a valuable tool in monitoring seagrass systems. This study investigated the efficacy of video photography as a tool for detecting change in seagrass cover, using the temperate Australian species Amphibolis antarctica (Labill.) Sonder ex Aschers. Using visual and random point estimates of seagrass cover from video footage, it was possible to determine the minimum sample size (number of random video frames) needed to detect change in seagrass cover, the minimum detectable change in cover and the probability of the monitoring design committing a Type II error. Video footage was examined at three scales: transects (m apart), sites (km apart) and regions (tens of km apart). Using visual and random point estimation techniques, a minimum sample size of ten quadrats per transect was required to detect change in uniform and variable seagrass cover. With ten quadrats it was possible to identify a minimum detectable change in cover of 15% for uniform and 30% for variable seagrass cover. Power analysis was used to determine the probability of committing a Type II error from the data. Region level data had low power, corresponding to a high risk of committing a Type II error. Site and transect level data had high power corresponding to a low risk of committing a Type II error. Based on this study's data, managers using video to monitor for change in seagrass cover are advised to use data from the smaller scale, for example, site and transect level data. By using data from the smaller scale, managers will have a low risk of incorrectly concluding there has not been a disturbance when one has actually occurred.