Beyond compliance : project on an integrated systems approach for pest risk management in South East Asia

The Beyond Compliance project, which began in July 2011 with funding from the Standards and Trade Development Facility for 2 years, aims to enhance competency and confidence in the South East Asian sub-region by applying a Systems Approach for pest risk management. The Systems Approach involves the use of integrated measures, at least two of which are independent, that cumulatively reduce the risk of introducing exotic pests through trade. Although useful in circumstances where single measures are inappropriate or unavailable, the Systems Approach is inherently more complicated than single-measure approaches, which may inhibit its uptake. The project methodology is to take prototype decision-support tools, such as Control Point-Bayesian Networks (CP-BN), developed in recent plant health initiatives in other regions, including the European PRATIQUE project, and to refine them within this sub-regional context. Case studies of high-priority potential agricultural trade will be conducted by National Plant Protection Organizations of participating South East Asian countries in trials of the tools, before further modifications. Longer term outcomes may include: more robust pest risk management in the region (for exports and imports); greater inclusion of stakeholders in development of pest risk management plans; increased confidence in trade negotiations; and new opportunities for trade.

The 10 Australian ecosystems most vulnerable to tipping points

We identify the 10 major terrestrial and marine ecosystems in Australia most vulnerable to tipping points, in which modest environmental changes can cause disproportionately large changes in ecosystem properties. To accomplish this we independently surveyed the coauthors of this paper to produce a list of candidate ecosystems, and then refined this list during a 2-day workshop. The list includes (1) elevationally restricted mountain ecosystems, (2) tropical savannas, (3) coastal floodplains and wetlands, (4) coral reefs, (5) drier rainforests, (6) wetlands and floodplains in the Murray-Darling Basin, (7) the Mediterranean ecosystems of southwestern Australia, (8) offshore islands, (9) temperate eucalypt forests, and (10) salt marshes and mangroves. Some of these ecosystems are vulnerable to widespread phase-changes that could fundamentally alter ecosystem properties such as habitat structure, species composition, fire regimes, or carbon storage. Others appear susceptible to major changes across only part of their geographic range, whereas yet others are susceptible to a large-scale decline of key biotic components, such as small mammals or stream-dwelling amphibians. For each ecosystem we consider the intrinsic features and external drivers that render it susceptible to tipping points, and identify subtypes of the ecosystem that we deem to be especially vulnerable. © 2011 Elsevier Ltd.

The distribution and spread of citrus canker in Emerald, Australia

Citrus canker is a disease of citrus and closely related species, caused by the bacterium Xanthomonas citri subsp. citri. This disease, previously exotic to Australia, was detected on a single farm [infested premise-1, (IP1). IP is the terminology used in official biosecurity protocols to describe a locality at which an exotic plant pest has been confirmed or is presumed to exist. IP are numbered sequentially as they are detected] in Emerald, Queensland in July 2004. During the following 10 months the disease was subsequently detected on two other farms (IP2 and IP3) within the same area and studies indicated the disease first occurred on IP1 and spread to IP2 and IP3. The oldest, naturally infected plant tissue observed on any of these farms indicated the disease was present on IP1 for several months before detection and established on IP2 and IP3 during the second quarter (i.e. autumn) 2004. Transect studies on some IP1 blocks showed disease incidences ranged between 52 and 100% (trees infected). This contrasted to very low disease incidence, less than 4% of trees within a block, on IP2 and IP3. The mechanisms proposed for disease spread within blocks include weather-assisted dispersal of the bacterium (e.g. wind-driven rain) and movement of contaminated farm equipment, in particular by pivot irrigator towers via mechanical damage in combination with abundant water. Spread between blocks on IP2 was attributed to movement of contaminated farm equipment and/or people. Epidemiology results suggest: (i) successive surveillance rounds increase the likelihood of disease detection; (ii) surveillance sensitivity is affected by tree size; and (iii) individual destruction zones (for the purpose of eradication) could be determined using disease incidence and severity data rather than a predefined set area.

Improving detection probabilities for pests in stored grains

BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grains, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper we demonstrate a sampling methodology that accounts for the heterogeneous distribution of insects in bulk grains. RESULTS: We show that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling program to detect insects in bulk grains. Our results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. We also demonstrate that the probability of detecting pests in bulk grains increases as the number of sub-samples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION: This study demonstrates the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

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.

Comparison of scoring systems for invasive pests using ROC analysis and Monte Carlo simulation

Different international plant protection organisations advocate different schemes for conducting pest risk assessments. Most of these schemes use structured questionnaire in which experts are asked to score several items using an ordinal scale. The scores are then combined using a range of procedures, such as simple arithmetic mean, weighted averages, multiplication of scores, and cumulative sums. The most useful schemes will correctly identify harmful pests and identify ones that are not. As the quality of a pest risk assessment can depend on the characteristics of the scoring system used by the risk assessors (i.e., on the number of points of the scale and on the method used for combining the component scores), it is important to assess and compare the performance of different scoring systems. In this article, we proposed a new method for assessing scoring systems. Its principle is to simulate virtual data using a stochastic model and, then, to estimate sensitivity and specificity values from these data for different scoring systems. The interest of our approach was illustrated in a case study where several scoring systems were compared. Data for this analysis were generated using a probabilistic model describing the pest introduction process. The generated data were then used to simulate the outcome of scoring systems and to assess the accuracy of the decisions about positive and negative introduction. The results showed that ordinal scales with at most 5 or 6 points were sufficient and that the multiplication-based scoring systems performed better than their sum-based counterparts. The proposed method could be used in the future to assess a great diversity of scoring systems.

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.

Russian wheat aphids (Diuraphis noxia) in China : native range expansion or recent introduction?

In this study, we explore the population genetics of the Russian wheat aphid (RWA) (Diuraphis noxia), one of the world’s most invasive agricultural pests, in north-western China. We have analysed the data of 10 microsatellite loci and mitochondrial sequences from 27 populations sampled over 2 years in China. The results confirm that the RWAs are holocyclic in China with high genetic diversity indicating widespread sexual reproduction. Distinct differences in microsatellite genetic diversity and distribution revealed clear geographic isolation between RWA populations in northern and southern Xinjiang, China, with gene flow interrupted across extensive desert regions. Despite frequent grain transportation from north to south in this region, little evidence for RWA translocation as a result of human agricultural activities was found. Consequently, frequent gene flow among northern populations most likely resulted from natural dispersal, potentially facilitated by wind currents. We also found evidence for the longterm existence and expansion of RWAs in China, despite local opinion that it is an exotic species only present in China since 1975. Our estimated date of RWA expansion throughout China coincides with the debut of wheat domestication and cultivation practices in western Asia in the Holocene. We conclude that western China represents the limit of the far eastern native range of this species. This study is the most comprehensive molecular genetic investigation of the RWA in its native range undertaken to date and provides valuable insights into the history of the association of this aphid with domesticated cereals and wild grasses.

Plastic traits of an exotic grass contribute to its abundance but are not always favourable

In herbaceous ecosystems worldwide, biodiversity has been negatively impacted by changed grazing regimes and nutrient enrichment. Altered disturbance regimes are thought to favour invasive species that have a high phenotypic plasticity, although most studies measure plasticity under controlled conditions in the greenhouse and then assume plasticity is an advantage in the field. Here, we compare trait plasticity between three co-occurring, C 4 perennial grass species, an invader Eragrostis curvula, and natives Eragrostis sororia and Aristida personata to grazing and fertilizer in a three-year field trial. We measured abundances and several leaf traits known to correlate with strategies used by plants to fix carbon and acquire resources, i.e. specific leaf area (SLA), leaf dry matter content (LDMC), leaf nutrient concentrations (N, C:N, P), assimilation rates (Amax) and photosynthetic nitrogen use efficiency (PNUE). In the control treatment (grazed only), trait values for SLA, leaf C:N ratios, Amax and PNUE differed significantly between the three grass species. When trait values were compared across treatments, E. curvula showed higher trait plasticity than the native grasses, and this correlated with an increase in abundance across all but the grazed/fertilized treatment. The native grasses showed little trait plasticity in response to the treatments. Aristida personata decreased significantly in the treatments where E. curvula increased, and E. sororia abundance increased possibly due to increased rainfall and not in response to treatments or invader abundance. Overall, we found that plasticity did not favour an increase in abundance of E. curvula under the grazed/fertilized treatment likely because leaf nutrient contents increased and subsequently its' palatability to consumers. E. curvula also displayed a higher resource use efficiency than the native grasses. These findings suggest resource conditions and disturbance regimes can be manipulated to disadvantage the success of even plastic exotic species.

Experimental evaluation of the culture performance of three exotic and a ‘local’ Giant Freshwater Prawn (Macrobrachium rosenbergii, De Man 1879) culture strain in Fiji

Giant freshwater prawn (GFP; Macrobrachium rosenbergii) aquaculture has expanded rapidly since 1990. Most local culture industries, however, have developed in an unsystematic way. Fiji has a small culture industry producing the ‘Anuenue’ strain; however, performance of this strain has never been systematically evaluated. Recently, some Fijian farmers have reported declines in stock productivity. The current project evaluated the relative performance of three exotic strains with different genetic backgrounds from Malaysia, Indonesia and Vietnam, against the ‘local’ strain in Fiji in a 4 × 3 replicated pond trial experiment. A total of 5827 prawns were harvested after 143 days growout. Individual growth rate and relative survival of the Fiji strain were not statistically different from any of the introduced strains, but Vietnam strain was superior to that of the Malaysia strain. Genetic diversity showed significant differences in variability among strains, with the Malaysian strain displaying the lowest genetic diversity. Indonesia strain showed that females were reaching maturation earlier than other strains and were smaller in size. This study suggests that Malaysian and Indonesian strains would constitute a poor choice for Fiji, whereas the Vietnam strain consistently performed well on all criteria measured. High variation among replicate ponds within strains unfortunately confounded among-strain variation.

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.