Multiannual infestation patterns of grapevine plant inhabitingScaphoideus titanus(Hemiptera: Cicadellidae) leafhoppers

Abstract

The Nearctic leafhopperScaphoideus titanusBall (Hemiptera: Cicadellidae) was accidentally introduced in Europe, where it became the vector of the ‘Candidatus Phytoplasma vitis’ phytoplasma causing the ‘Flavescence dorée’ disease of grapevine plants. A time-varying distributed delay model, simulating the successive occurrences of egg hatching, nymph presence, and adult emergence, is extended here to represent multi-generation infestation patterns of grapevine plants inhabited by eggs, nymphs, and adults. The model extension includes intrinsic mortality, mortality caused by plant dormancy, and low temperatures, development of diapausing and post-diapausing eggs, fecundity rates, and adult longevity. Field observations and published data were used to estimate parameters. The model was validated with five years canopy infestation data from five vineyards not subjected to insecticide treatments and found to have satisfactory explicative and predictive qualities. The model output is most sensitive to a 10% variation in the upper threshold and in the shape parameters of the survivorship function and least sensitive to a 10% variation in the shape parameters of the development function and the survivorship level. Recommendations are made to take into account other factors than temperature and plant phenology and include a wider geographical area in further model development.

Space-Time Point Pattern Analysis of Flavescence Dorée Epidemic in a Grapevine Field: Disease Progression and Recovery

“…Note that rows themselves may have affected the wind direction, thus a superposition of effects due to row and forced wind direction may have accentuated FD preferential propagation direction. Factors such as temperature and plant phenology are known to have an impact on the development rate of S. titanus (Rigamonti et al, 2013). Hence, all these factors may play a role in determining the epidemic isotropicity from field to regional scale, and could be modified in order to minimize the disease spread.…”

“…FD affects S. titanus fitness (Bressan et al, 2005a), and this can therefore introduce nonlinear feedbacks on its reproduction, and movement in space and over time, hence on FD spread. The complex features of the FD epidemics, including acquisition and transmission, latency in vector insect and host plant, and fitness effects on vector and host, have been explored by mathematical descriptions of FD dynamics and epidemiology in various recent works (Rigamonti et al, 2011, 2013; Maggi et al, 2013, 2014a,b; Lessio et al, 2015) and have provided indicative explanations of the large temporal heterogeneity in FD outbreaks not only over regional scales but also from site to site in the same region. Earlier analyses have highlighted the relatively sparse nature of S. titanus after aggregated counting at intra and regional scales (Linder and Jermini, 2007; Seljak, 2008).…”

“…This opens a number of questions on whether methods to measure the degree of randomness should be implemented at multiple scales, and whether various methods should be applied. Although there is no epidemiological mapping over regional-to-continental areas of the FD progression that uses symptoms observed in individual plants, data exists over the field scale (e.g., Morone et al, 2007; Pavan et al, 2012; Rigamonti et al, 2013). It is therefore possible to retrieve space-time point pattern statistics that may highlight advances in heterogeneity of FD epidemics and trends in its progression and regression using diverse methods.…”

Biology and ecology of the Flavescence dorée vector Scaphoideus titanus: a review

“…Models to improve the understanding of the spatiotemporal population and pattern of infective vector dynamics were developed. Most of them are phenology models that predict the dynamics of age structure, the beginning and the pattern of egg hatching, the occurrence of nymphal instars, and the emergence of adults (Rigamonti et al 2011;Maggi et al 2013;Rigamonti et al 2013b). Others focused on biological parameters like the sex ratio , the seasonal progression of the proportion of infective vectors (Bressan et al 2006;, and the relationship between S. titanus population levels and diseased grapevines in the following year (Morone et al 2007).…”

Conventional and novel approaches for managing “flavescence dorée” in grapevine: knowledge gaps and future prospects

“…() developed a phenology model to improve understanding of insect–vineyard dynamics and to improve the timing of applications of an insect growth regulator, considering the development of insect eggs, nymph instars and their transition to the adult stage. This model was improved after the discovery of the importance of temperature during oviposition (Rigamonti et al ., ,b). Lessio et al .…”