Quarantine and surveillance strategies for plant pathogen detection and control

Incursions of plant pests and diseases pose serious threats to food security, agricultural productivity and the natural environment. One of the challenges in confidently delimiting and eradicating incursions is how to choose from an arsenal of surveillance and quarantine approaches in order to best control multiple dispersal pathways. Anthropogenic spread (propagules carried on humans or transported on produce or equipment) can be controlled with quarantine measures, which in turn can vary in intensity. In contrast, environmental spread processes are more difficult to control, but often have a temporal signal (e.g. seasonality) which can introduce both challenges and opportunities for surveillance and control. This leads to complex decisions regarding when, where and how to search. Recent modelling investigations of surveillance performance have optimised the output of simulation models, and found that a risk-weighted randomised search can perform close to optimally. However, exactly how quarantine and surveillance strategies should change to reflect different dispersal modes remains largely unaddressed. Here we develop a spatial simulation model of a plant fungal-pathogen incursion into an agricultural region, and its subsequent surveillance and control. We include structural differences in dispersal via the interplay of biological, environmental and anthropogenic connectivity between host sites (farms). Our objective was to gain broad insights into the relative roles played by different spread modes in propagating an invasion, and how incorporating knowledge of these spread risks may improve approaches to quarantine restrictions and surveillance. We find that broad heuristic rules for quarantine restrictions fail to contain the pathogen due to residual connectivity between sites, but surveillance measures enable early detection and successfully lead to suppression of the pathogen in all farms. Alternative surveillance strategies attain similar levels of performance by incorporating environmental or anthropogenic dispersal risk in the prioritisation of sites. Our model provides the basis to develop essential insights into the effectiveness of different surveillance and quarantine decisions for fungal pathogen control. Parameterised for authentic settings it will aid our understanding of how the extent and resolution of interventions should suitably reflect the spatial structure of dispersal processes.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

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.

Specimen-based databases of Australian plant pathogens: past, present and future

Specimen-based records of most of the plant pathogens that occur in Australia can be accessed through the Australian Plant Disease Database and the Australian Plant Pest Database. These databases and the herbaria that underpin them are important resources for resolving quarantine and trade issues as well as for the diagnosis of plant diseases. The importance of these collections and databases to Australia's agricultural industries is discussed.

A one-tube fluorescent assay for the quarantine detection and identification of Tilletia indica and other grass bunts in wheat

A molecular assay with enhanced specificity and sensitivity has been developed to assist in the surveillance of Karnal bunt, a quarantineable disease with a significant impact on international trade. The protocol involves the release of DNA from spores, PCR amplification to enrich Tilletia-specific templates from released DNA and a five-plex, real-time PCR assay to detect, identify and distinguish T. indica and other Tilletia species (T. walkeri, T. ehrhartae, T. horrida and a group comprising T. caries, T. laevis, T. contraversa, T. bromi and T. fusca) in wheat grains. This fluorescent molecular tool has a detection sensitivity of one spore and thus bypasses the germination step, which in the current protocol is required for confirmation when only a few spores have been found in grain samples. The assay contains five dual-labelled, species-specific probes and associated species-specific primer pairs in a PCR mix in one tube. The different amplification products are detected simultaneously by five different fluorescence spectra. This specific and sensitive assay with reduced labour and reagent requirements makes it an effective and economically sustainable tool to be used in a Karnal bunt surveillance program. This protocol will also be valuable for the identification of some contaminant Tilletia sp. in wheat grains.

Predicting risk and benefit a priori in biological control of invasive plant species: a systems modelling approach

While the method using specialist herbivores in managing invasive plants (classical biological control) is regarded as relatively safe and cost-effective in comparison to other methods of management, the rarity of strict monophagy among insect herbivores illustrates that, like any management option, biological control is not risk-free. The challenge for classical biological control is therefore to predict risks and benefits a priori. In this study we develop a simulation model that may aid in this process. We use this model to predict the risks and benefits of introducing the chrysomelid beetle Charidotis auroguttata to manage the invasive liana Macfadyena unguis-cati in Australia. Preliminary host-specificity testing of this herbivore indicated that there was limited feeding on a non-target plant, although the non-target was only able to sustain some transitions of the life cycle of the herbivore. The model includes herbivore, target and non-target life history and incorporates spillover dynamics of populations of this herbivore from the target to the non-target under a variety of scenarios. Data from studies of this herbivore in the native range and under quarantine were used to parameterize the model and predict the relative risks and benefits of this herbivore when the target and non-target plants co-occur. Key model outputs include population dynamics on target (apparent benefit) and non-target (apparent risk) and fitness consequences to the target (actual benefit) and non-target plant (actual risk) of herbivore damage. The model predicted that risk to the non-target became unacceptable (i.e. significant negative effects on fitness) when the ratio of target to non-target in a given patch ranged from 1:1 to 3:2. By comparing the current known distribution of the non-target and the predicted distribution of the target we were able to identify regions in Australia where the agent may be pose an unacceptable risk. By considering risk and benefit simultaneously, we highlight how such a simulation modelling approach can assist scientists and regulators in making more objective decisions a priori, on the value of releasing specialist herbivores as biological control agents.

Characterising insect plant host relationships facilitates understanding multiple host use

Weed biocontrol relies on host specificity testing, usually carried out under quarantine conditions to predict the future host range of candidate control agents. The predictive power of host testing can be scrutinised directly with Aconophora compressa, previously released against the weed Lantana camara L. (lantana) because its ecology in its new range (Australia) is known and includes the unanticipated use of several host species. Glasshouse based predictions of field host use from experiments designed a posteriori can therefore be compared against known field host use. Adult survival, reproductive output and egg maturation were quantified. Adult survival did not differ statistically across the four verbenaceous hosts used in Australia. Oviposition was significantly highest on fiddlewood (Citharexylum spinosum L.), followed by lantana, on which oviposition was significantly higher than on two varieties of Duranta erecta (‘‘geisha girl’’ and ‘‘Sheena’s gold’’; all Verbenaceae). Oviposition rates across Duranta varieties were not significantly different from each other but were significantly higher than on the two non-verbenaceous hosts (Jacaranda mimosifolia D. Don: Bignoneaceae (jacaranda) and Myoporum acuminatum R. Br.: Myoporaceae (Myoporum)). Production of adult A. compressa was modelled across the hosts tested. The only major discrepancy between model output and their relative abundance across hosts in the field was that densities on lantana in the field were much lower than predicted by the model. The adults may, therefore, not locate lantana under field conditions and/or adults may find lantana but leave after laying relatively few eggs. Fiddlewood is the only primary host plant of A. compressa in Australia, whereas lantana and the others are used secondarily or incidentally. The distinction between primary, secondary and incidental hosts of a herbivore species helps to predict the intensity and regularity of host use by that herbivore. Populations of the primary host plants of a released biological control agent are most likely to be consistently impacted by the herbivore, whereas secondary and incidental host plant species are unlikely to be impacted consistently. As a consequence, potential biocontrol agents should be released only against hosts to which they have been shown to be primarily adapted.

Relative host plant species use by the lantana biological control agent Aconophora compressa (Membracidae) across its native and introduced ranges

Aconophora compressa Walker (Hemiptera: Membracidae) was released in 1995 against the weed lantana in Australia, and is now found on multiple host plant species. The intensity and regularity at which A. compressa uses different host species was quantified in its introduced Australian range and also its native Mexican range. In Australia, host plants fell into three statistically defined categories, as indicated by the relative rates and intensities at which they were used in the field. Fiddlewood (Citharexylum spinosum L.: Verbenaceae) was used much more regularly and at higher densities than any other host sampled, and alone made up the first group. The second group, lantana (Lantana camara L.: Verbenaceae; pink variety) and geisha girl (Duranta erecta L.: Verbenaceae), were used less regularly and at much lower densities than fiddlewood. The third group, Sheena’s gold (another variety of D. erecta), jacaranda (Jacaranda mimosifolia D. Don: Bignoniaceae) and myoporum (Myoporum acuminatum R. Br.: Myoporaceae), were used infrequently and at even lower densities. In Mexico, the insect was found at relatively low densities on all hosts relative to those in Australia. Densities were highest on L. urticifolia, D. erecta and Tecoma stans (L.) Juss. ex Kunth (Bignoniaceae), which were used at similar rates to one another. It was found also on a few other verbenaceous and non-verbenaceous host species but at even lower densities. The relative rate at which Citharexylum spp. and L. urticifolia were used could not be assessed in Mexico because A. compressa was found on only one plant of each species in areas where these host species co-occurred. The low rate at which A. compressa occurred on fiddlewood in Mexico is likely to be an artefact of the short-term nature of the surveys or differences in the suites of Citharexylum and Lantana species available there. These results provide further incentive to insist on structured and quantified surveys of non-target host use in the native range of potential biological control agents prior to host testing studies in quarantine.

CRC40142 Defining the plant pathogen risk posed by international travellers

This project will define the plant pathogen incursion risk posed by people returning from overseas and interstate travel. This will be achieved through the development of technically sound sample/survey methodologies. The project will initially focus on cereal rusts. An assessment of the current level of human mediated rust entries into Australia will be determined through the sampling of travellers who have been known to have visited grain production regions overseas.

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.

Hierarchical Bayesian modelling of plant pest invasions with human-mediated dispersal

Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.

Australia's newest quarantine for biological control

The paper describes the QC3 quarantine facility and supporting infrastructure which were purpose built for weed biological control at the Ecosciences Precinct. The quarantine is one of two new weed quarantine facilities in Australia and will service northern Australia. An account of the sharing philosophy between CSIRO and the Queensland Government and the necessity of working very closely with architects, project managers, builders and quarantine personnel is also given. This philosophy contributed to certification of the facility without any undue delays.

Exotic plant pests–a threat to the sustainability of Australia’s grains industry

Exotic plant pests (EPPs) threaten production, market access and sustainability of Australian plant production systems. For the grains industry there are over 600 identified EPPs of which 54 are considered high priority, posing a significant threat. Despite Australia’s geographical isolation and strong quarantine systems, the threat from EPPs has never been higher with the increasing levels of travel and trade, emphasising the need for improving our efforts in prevention, preparedness and surveillance for EPPs.

Low-dose methyl bromide fumigation as a quarantine disinfestation treatment for nectarines against Queensland fruit fly (Diptera:Tephritidae)

White nectarines (Prunus persica var. nucipersica) were fumigated with methyl bromide (MB) at a nominal treatment dose of 18 g m-3 at 18°C for 5 h and 30 min as a quarantine disinfestation treatment against Bactrocera tryoni, the Queensland fruit fly. Three large scale trials were conducted against each of the four immature lifestages, eggs and first, second and third instars. There were no survivors from the estimated 43,614 eggs, 41,873 first instars, 41,345 second instars and 33,549 third instars treated, thereby resulting in an efficacy of GROTERDAN99.99% mortality at the 95% confidence level for each lifestage. Of the 12 trials reported herein, the highest concentration of MB, sampled from the chamber headspace analysed by gas chromatography, was 18.7 g m-3. The maximum chamber temperature from 5 min readings was 19.7°C and the maximum fruit core temperature was 19.5°C. The treatment time for all trials was exactly 5.5 h. Thus the recommended treatment dose to disinfest nectarines from B. tryoni is 19.0 g m-3 MB at 20.0°C for 5.5 h. Fruit quality trials were conducted on white nectarines at three combinations of treatment parameters: 15 g m-3 MB at 19°C for 5.25 h; 18 g m-3 MB at 19°C for 5.5 h and 21 g m-3 MB at 19°C for 5.5 h. The fruit were stored at 0, 4 and 8 days at 4°C and 8 days at 4°C followed by 4 d at 22°C. They were then were assessed for skin colour, flesh colour, skin defects, flesh defects, fruit weight loss, flesh firmness, total soluble solids, titratable acidity and rots. There was no significant difference between untreated control and MB treated fruits in any of the parameters measured. Thus the treatments did not have adverse effects on fruit quality.