Molecular Assessment of the Introduction and Spread of Potato Cyst Nematode, Globodera rostochiensis, in Victoria, Australia.

Potato cyst nematodes (PCN) are damaging soilborne quarantine pests of potato in many parts of the world. There are two recognized species, Globodera pallida and G. rostochiensis, with only the latter species-the golden cyst nematode-present in Australia. PCN was first discovered in Australia in 1986 in Western Australia, where it was subsequently eradicated and area freedom for market access was reinstated. In Victoria, PCN was first detected in 1991 east of Melbourne. Since then, it has been found in a small number of localized regions to the south and east. Strict quarantine controls have been in place since each new detection. It has previously been speculated that there were multiple separate introductions of PCN into Victoria. Our study utilized a historic (years 2001 to 2014) PCN cyst reference collection to examine genetic variability of Victorian PCN populations to investigate potential historical origins and subsequent changes in the populations that might inform patterns of spread. DNA was extracted from single larvae dissected from eggs within cysts and screened using nine previously described polymorphic microsatellite markers in two multiplex polymerase chain reaction assays. Sequence variation of the internal transcribed spacer region of the DNA was also assessed and compared with previously published data. A hierarchical sampling strategy was used, comparing variability of larvae within cysts, within paddocks, and between local regions. This sampling revealed very little differentiation between Victorian populations, which share the same microsatellite allelic variation, with differences between local regions probably reflecting changes in allele frequencies over time. Our molecular assessment supports a probable single localized introduction into Victoria followed by limited spread to nearby areas. The Australian PCN examined appear genetically distinct from populations previously sampled worldwide; thus, any new exotic incursions, potentially bringing in additional PCN pathotypes, should be easily differentiated from existing established local PCN populations.

Accounting for spatially heterogeneous conditions in local-scale surveillance strategies: case study of the biosecurity insect pest, grape phylloxera (Daktulosphaira vitifoliae (Fitch)).

BACKGROUND: Surveillance strategies are often standardized and completed on grid patterns to detect pest incursions quickly; however, it may be possible to improve surveillance through more targeted observation that accounts for landscape heterogeneity, dispersal and the habitat requirements of the invading organism. We simulated pest spread at a local scale, using grape phylloxera (Daktulosphaira vitifoliae (Fitch)) as a case study, and assessed the influence of incorporating spatial heterogeneity into surveillance compared with current, standard surveillance strategies. RESULTS: Time to detection and spread within and beyond the vineyard were reduced by conducting surveys that target sampling effort in soil that is highly suitable for the invading pest in comparison with standard surveillance strategies. However, these outcomes were dependent on the virulence level of phylloxera because phylloxera is a complex pest with multiple genotypes that influence spread and detectability. CONCLUSION: Targeting surveillance strategies based on local-scale spatial heterogeneity can decrease the time to detection without increasing the survey cost, and surveillance that targets highly suitable soil is the most efficient strategy for detecting new incursions. In addition, combining targeted surveillance strategies with buffer zones and hygiene procedures, and updating surveillance strategies as additional species information becomes available, will further decrease the risk of pest spread. © 2018 Society of Chemical Industry.

Do an invasive organism's dispersal characteristics affect how we should search for it?

We investigated how an invading organism's dispersal characteristics affect the efficacy of different surveillance strategies aimed at detecting that organism as it spreads following a new incursion. Specifically, we assessed whether, out of the surveillance strategies tested, the best surveillance strategy for an organism varied depending on the way it disperses. We simulated the spread of invasive organisms with different dispersal characteristics including leptokurtic and non-leptokurtic kernels with different median dispersal distances and degrees of kurtosis. We evaluated surveillance strategies with different sampling arrangements, densities and frequencies. Surveillance outcomes compared included the time to detection, the total spread of the invasion and the likelihood of the invasion reaching new areas. Overall, dispersal characteristics affected the surveillance outcomes, but the grid surveillance arrangement consistently performed best in terms of early detection and reduced spread within and between fields. Additionally, the results suggest that dispersal characteristics may influence spread to new areas and surveillance strategies. Therefore, knowledge on an invasive organism's dispersal characteristics may influence how we search for it and how we manage the invasion to prevent spread to new areas.