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.

Pseudoseeds : investigating long-distance, ocean seed dispersal with wireless sensors

Recent theoretical research has shown that ocean currents and wind interact to disperse seeds over long distances among isolated landmasses. Dispersal of seeds among isolated oceanic islands, by birds, oceans and man, is a well-known phenomenon, and many widespread island plants have traits that facilitate this process. Crucially, however, there have been no mechanistic vector-based models of long-distance dispersal for seeds among isolated oceanic islands based on empirical data. Here, we propose a plan to develop seed analogues, or pseudoseeds, fitted with wireless sensor technology that will enable high-fidelity tracking as they disperse across the ocean. The pseudoseeds will be precisely designed to mimic actual seed buoyancy and morphology enabling realistic and accurate, vector-based dispersal models of ocean seed dispersal over vast geographic scales.

Simple rules to contain an invasive species with a complex life cycle and high dispersal capacity

Designing practical rules for controlling invasive species is a challenging task for managers, particularly when species are long-lived, have complex life cycles and high dispersal capacities. Previous findings derived from plant matrix population analyses suggest that effective control of long-lived invaders may be achieved by focusing on killing adult plants. However, the cost-effectiveness of managing different life stages has not been evaluated. We illustrate the benefits of integrating matrix population models with decision theory to undertake this evaluation, using empirical data from the largest infestation of mesquite (Leguminosae: Prosopis spp) within Australia. We include in our model the mesquite life cycle, different dispersal rates and control actions that target individuals at different life stages with varying costs, depending on the intensity of control effort. We then use stochastic dynamic programming to derive cost-effective control strategies that minimize the cost of controlling the core infestation locally below a density threshold and the future cost of control arising from infestation of adjacent areas via seed dispersal. Through sensitivity analysis, we show that four robust management rules guide the allocation of resources between mesquite life stages for this infestation: (i) When there is no seed dispersal, no action is required until density of adults exceeds the control threshold and then only control of adults is needed; (ii) when there is seed dispersal, control strategy is dependent on knowledge of the density of adults and large juveniles (LJ) and broad categories of dispersal rates only; (iii) if density of adults is higher than density of LJ, controlling adults is most cost-effective; (iv) alternatively, if density of LJ is equal or higher than density of adults, management efforts should be spread between adults, large and to a lesser extent small juveniles, but never saplings. Synthesis and applications.In this study, we show that simple rules can be found for managing invasive plants with complex life cycles and high dispersal rates when population models are combined with decision theory. In the case of our mesquite population, focussing effort on controlling adults is not always the most cost-effective way to meet our management objective.

Trans-Bass Strait speciation and trans-Pacific dispersal in the Myoporum thrips (Thysanoptera, Phlaeothripinae)

Molecular and morphological data indicate that the pest thrips damaging Myoporum species in California and Hawai'i, Klambothrips myoporiMound and Morris, originated in Tasmania, Australia. This trans-Pacific dispersal presumably resulted from the international horticultural trade in Myoporum species. The data distinguish the pest from K. adelaideae sp.n. that induces leaf deformation on M. insulare along the coast of mainland Australia that is separated by ∼300km from Tasmania by the Bass Strait. K. myopori is more damaging to its non-native hosts in California and Hawai'i than to M. insulare in Tasmania, and further research is needed to determine if this is the result of release from its natural enemies. However, in certain areas of California, some Myoporum species are invasive weeds, and K. myopori may be considered an example of an accidental but beneficial introduction in this instance because of its detrimental impact on the plant species.

A continent-wide study reveals clear relationships between regional abiotic conditions and post-dispersal seed predation

Aim Large-scale patterns linking energy availability, biological productivity and diversity form a central focus of ecology. Despite evidence that the activity and abundance of animals may be limited by climatic variables associated with regional biological productivity (e.g. mean annual precipitation and annual actual evapotranspiration), it is unclear whether plant–granivore interactions are themselves influenced by these climatic factors across broad spatial extents. We evaluated whether climatic conditions that are known to alter the abundance and activity of granivorous animals also affect rates of seed removal. Location Eleven sites across temperate North America. Methods We used a common protocol to assess the removal of the same seed species (Avena sativa) over a 2-day period. Model selection via the Akaike information criterion was used to determine a set of candidate binomial generalized linear mixed models that evaluated the relationship between local climatic data and post-dispersal seed predation. Results Annual actual evapotranspiration was the single best predictor of the proportion of seeds removed. Annual actual evapotranspiration and mean annual precipitation were both positively related to mean seed removal and were included in four and three of the top five models, respectively. Annual temperature range was also positively related to seed removal and was an explanatory variable in three of the top four models. Main conclusions Our work provides the first evidence that energy and precipitation, which are known to affect consumer abundance and activity, also translate to strong, predictable patterns of seed predation across a continent. More generally, these findings suggest that future changes in temperature and precipitation could have widespread consequences for plant species composition in grasslands, through impacts on plant recruitment.

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.

Sexual selection in a tropical fruit fly : role of a plant derived chemical in mate choice

The specific mechanisms by which selective pressures affect individuals are often difficult to resolve. In tephritid fruit flies, males respond strongly and positively to certain plant derived chemicals. Sexual selection by female choice has been hypothesized as the mechanism driving this behaviour in certain species, as females preferentially mate with males that have fed on these chemicals. This hypothesis is, to date, based on studies of only very few species and its generality is largely untested. We tested the hypothesis on different spatial scales (small cage and seminatural field-cage) using the monophagous fruit fly, Bactrocera cacuminata. This species is known to respond to methyl eugenol (ME), a chemical found in many plant species and one upon which previous studies have focused. Contrary to expectation, no obvious female choice was apparent in selecting ME-fed males over unfed males as measured by the number of matings achieved over time, copulation duration, or time of copulation initiation. However, the number of matings achieved by ME-fed males was significantly greater than unfed males 16 and 32 days after exposure to ME in small cages (but not in a field-cage). This delayed advantage suggests that ME may not influence the pheromone system of B. cacuminata but may have other consequences, acting on some other fitness consequence (e.g., enhancement of physiology or survival) of male exposure to these chemicals. We discuss the ecological and evolutionary implications of our findings to explore alternate hypotheses to explain the patterns of response of dacine fruit flies to specific plant-derived chemicals.

Influence of host plant structure and microclimate on the abundance and behaviour of Tephritid fly

Microclimate and host plant architecture significantly influence the abundance and behavior of insects. However, most research in this field has focused at the invertebrate assemblage level, with few studies at the single-species level. Using wild Solanum mauritianum plants, we evaluated the influence of plant structure (number of leaves and branches and height of plant) and microclimate (temperature, relative humidity, and light intensity) on the abundance and behavior of a single insect species, the monophagous tephritid fly Bactrocera cacuminata (Hering). Abundance and oviposition behavior were signficantly influenced by the host structure (density of foliage) and associated microclimate. Resting behavior of both sexes was influenced positively by foliage density, while temperature positively influenced the numbers of resting females. The number of ovipositing females was positively influenced by temperature and negatively by relative humidity. Feeding behavior was rare on the host plant, as was mating. The relatively low explanatory power of the measured variables suggests that, in addition to host plant architecture and associated microclimate, other cues (e.g., olfactory or visual) could affect visitation and use of the larval host plant by adult fruit flies. For 12 plants observed at dusk (the time of fly mating), mating pairs were observed on only one tree. Principal component analyses of the plant and microclimate factors associated with these plants revealed that the plant on which mating was observed had specific characteristics (intermediate light intensity, greater height, and greater quantity of fruit) that may have influenced its selection as a mating site.