Are insect frugivores always plant pests? The impact of fruit fly (Diptera: Tephritidae) larvae on host plant fitness

Herbivory is generally regarded as negatively impacting on host plant fitness. Frugivorous insects, which feed directly on plant reproductive tissues, are predicted to be particularly damaging to hosts. We tested this prediction with the fruit fly, Bactrocera tryoni, by recording the impact of larval feeding on two direct (seed number and germination) and two indirect (fruit decay rate and attraction/deterrence of vertebrate frugivores) measures of host plant fitness. Experiments were done in the laboratory, glasshouse and tropical rainforest. We found no negative impact of larval feeding on seed number or germination for three test plants: tomato, capsicum and eggplant. Further, larval feeding accelerated the initiation of decay and increased the final level of fruit decay in tomatoes, apples, pawpaw and pear, a result considered to be beneficial to the fruit. In rainforest studies, native rodents preferred infested apple and pears compared to uninfested control fruit; however, there were no differences observed between treatments for tomato and pawpaw. For our study fruits, these results demonstrate that fruit fly larval infestation has neutral or beneficial impacts on the host plant, an outcome which may be largely influenced by the physical properties of the host. These results may contribute to explaining why fruit flies have not evolved the same level of host specialization generally observed for other herbivore groups.

CRC27012 A National Diagnostic Database for Emergency Plant Pests

Development of a national diagnostic database for Emergency Plant Pests which will be web-accessible.

Integrating drivers influencing the detection of plant pests carried in the international cut flower trade

This paper analyses the cut flower market as an example of an invasion pathway along which species of non-indigenous plant pests can travel to reach new areas. The paper examines the probability of pest detection by assessing information on pest detection and detection effort associated with the import of cut flowers. We test the link between the probability of plant pest arrivals as a precursor to potential invasion, and volume of traded flowers using count data regression models. The analysis is applied to the UK import of specific genera of cut flowers form Kenya between 1996 and 2004. There is a link between pest detection and the Genus of cut flower imported. Hence, pest detection efforts should focus on identifying and targeting those imported plants with a high risk of carrying pest species. For most of the plants studied efforts allocated to inspection have a significant influence on the probabilty of pest detction. However, by better targetting inspection efforts, it is shown that plant inspection effort could be reduced without increasing the risk of pest entry. Similarly, for most of the plants analysed, an increase in volume traded will not necessarily lead to an increase in the number of pests entering the UK. For some species, such as conclude that analysis at the rank of plant Genus is important both to understand the effectiveness of plant pest detection efforts and consequently to manage the risk of introduction of non-indigenous species.

Compensation for quarantined plant loss [microform] : protection against plant pests : hearing before the Subcommittee on Department Operations, Research, and Foreign Agriculture of the Committee on Agriculture, House of Representatives, Ninety-seventh Congress, first session, on H.R. 2159 and H.R. 4108, October 1, 1981.

"Serial no. 97-00."

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.

Development of a New Zealand database of plant virus and virus-like organisms.

The recent 8th Australasian plant virology workshop in Rotorua, New Zealand, discussed the development of a New Zealand database of plant virus and virus-like organisms. Key points of discussion included: (i) the purpose of such a database; (ii) who would benefit from the information in a database; (iii) the scope of a database and its associated collections; (iv) database information and format; and (v) potential funding of such a database. From the workshop and further research, we conclude that the preservation and verification of specimens within the collections and the development of a New Zealand database of plant virus and virus-like organisms is essential. Such a collection will help to fulfil statutory requirements in New Zealand and assist in fulfilling international obligations under the International Plant Protection Convention. Sustaining such a database will assist New Zealand virologists and statutory bodies to undertake scientifically sound research. Establishing reliable records and an interactive database will help to ensure accurate and timely diagnoses of diseases caused by plant viruses and virus-like organisms. Detection of new incursions and their diagnosis will be further enhanced by the use of such reference collections and their associated database. Connecting and associating this information to similar overseas databases would assist international collaborations and allow access to the latest taxonomic and diagnostic resources. Associated scientists working in the areas of plant breeding, export phytosanitary assurance and in the area of the conservation estate would also benefit from access to verified specimens of plant viruses and virus-like organisms. We conclude that funding of a New Zealand database of virus and virus-like organisms and its associated collections should be based partly on Crown funds, as it is a nationally significant biological resource.

Healthy hardwoods. A field guide to pests, diseases and nutritional disorders in subtropical hardwoods.

Healthy hardwoods: A field guide to pests, diseases and nutritional disorders in subtropical hardwoods can be used to help identify the common damaging insects, fungi and nutritional disorders in young eucalypt (Eucalyptus and Corymbia species) plantations in subtropical eastern Australia. This guide includes photographs of each insect, fungus and nutritional disorder and the damage they cause, along with a brief description to aid identification. A brief host list for insects and fungi, including susceptibility and occurrence, is provided as a guide only. A hand lens will be useful, especially to identify fungi. Although it is possible to identify insects and fungi from these photographs, laboratory examination will sometimes be necessary. For example, microscopes and culturing media might be used to identify fungi. Information about four exotic pests and diseases has also been included in the Biosecurity threats chapter. Potentially, these would have a severe impact on plantation and natural forests if introduced into Australia. To prevent establishment of these pests, early detection and identification is crucial. If an exotic insect or disease is suspected, then an immediate response is required. Usually, the first response will be to contact the nearest Australian Quarantine and Inspection Service office or forestry agency to seek advice.

Healthy plantations. A field guide to pests and pathogens of Acacia, Eucalyptus and Pinus in Vietnam.

This book is a resource for those involved ‘on-the-ground’ with growing plantation trees in Vietnam, identifying the pests and diseases found on them, and managing the impacts of these organisms. The book, supported by AusAID’s Vietnam CARD (Cooperation for Agricultural and Rural Development) Program, and draws on the collective, long-standing experience of forest health scientists in Vietnam, Australia and South Africa. The book provides illustrations and information on 23 pests and 25 diseases of Acacia, Eucalyptus and Pinus for Vietnam; four of these species are important biosecurity threats not yet present in Vietnam.

Pests and Diseases in Field Crops

Insect pest diagnostics.

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.