Factors Influencing Aster Leafhopper (Hemiptera: Cicadellidae) Abundance and Aster Yellows Phytoplasma Infectivity in Wisconsin Carrot Fields

Abstract

In Wisconsin, vegetable crops are threatened annually by infection of the aster yellows phytoplasma (AYp), the causal agent of aster yellows (AY) disease, vectored by the aster leafhopper, Macrosteles quadrilineatus Forbes. Aster leafhopper abundance and infectivity are influenced by processes operating across different temporal and spatial scales. We applied a multilevel modeling approach to partition variance in multifield, multiyear, pest scouting data sets containing temporal and spatial covariates associated with aster leafhopper abundance and infectivity. Our intent was to evaluate the relative importance of temporal and spatial covariates to infer the relevant scale at which ecological processes are driving AY epidemics and identify periods of elevated risk for AYp spread. The relative amount of aster leafhopper variability among and within years (39%) exceeded estimates of variation among farm locations and fields (7%). Similarly, time covariates explained the largest amount of variation of aster leafhopper infectivity (50%). Leafhopper abundance has been decreasing since 2001 and reached its minimum in 2010. The average seasonal pattern indicated that periods of above average abundance occurred between 11 June and 1 August. Annual infectivity appears to oscillate around an average value of 2% and seasonal periods of above average infectivity occur between 19 May and 15 July. The coincidence of the expected periods of high leafhopper abundance and infectivity increases our knowledge of when the insect moves into susceptible crop fields and when it spreads the pathogen to susceptible crops, representing a seasonal interval during which management of the insect can be focused.

Parasite co-opts a ubiquitin receptor to induce a plethora of developmental changes

“…Phytoplasma asteris) (Hogenhout et al, 2008; Sugio et al, 2011b; Zhang et al, 2004). The main vector of AYPs in North America is the polyphagous aster leafhopper Macrosteles quadrilineatus , which migrates over long distances and transmits the bacteria to various crops (Frost et al, 2013a, b). AYPs and M. quadrilineatus colonise a broad range of plant species, including oilseed rape and other members of the Brassicaceae , as well as lettuce, carrots and several cereals (CABI, 2021).…”

A Bacterial Parasite Effector Mediates Insect Vector Attraction in Host Plants Independently of Developmental Changes

“…The aster leafhopper M. quadrilineatus is the most important insect vector of the phyllody-inducing ‘ Ca . Phytoplasma asteris’ strain AY-WB ( Frost et al, 2011 , 2013 ). This leafhopper favors the colonization of plants with leaf-like flowers (phytoplasma-infected rad23bd mutant plants and GFP-SAP54 transgenic plants) versus plants with wild-type flowers (phytoplasma-infected rad23bcd mutant plants and GFP transgenic plants; MacLean et al, 2014 ).…”

“…Phytoplasmas depend on sap-feeding hemipteran insect vectors for transmission ( Weintraub and Beanland, 2006 ). For Aster Yellows strain Witches’ Broom (AY-WB) phytoplasma (‘ Candidatus ’ Phytoplasma asteris) it was found that infected plants are more attractive to the aster leafhopper Macrosteles quadrilineatus , which is the most important insect vector of AY-WB ( Frost et al, 2011 , 2013 ; Sugio et al, 2011a , b ). The two AY-WB virulence proteins (effectors) SAP11 and SAP54 modulate Arabidopsis thaliana development and promote attraction and reproduction of insect vectors to phytoplasma-infected A. thaliana plants ( MacLean et al, 2011 , 2014 ; Sugio et al, 2011a , b ).…”

Degree day models to forecast the seasonal phenology of Drosophila suzukii in tart cherry orchards in the Midwest U.S.

“…Modeling the seasonal population variations of pests from field monitoring data can help determine periods of high pest abundance [16]. Phenology models are particularly effective in describing the population dynamics of pests which maintain relatively few and synchronous generations during the year [17,18].…”

“…Previous research involving elucidating the phenology of insects through population modelling include the use of both linear [25], and additive models [13]. These models are implemented to help observe trends in species phenology, explore the influence abiotic factors have on populations dynamics, and provide general estimates of insect population intensity [13,16,20,25]. In general, GAM models are able to estimate different DD's corresponding to phenological events such as first detection or peak activity, and GLM models have the capacity to produce trap catch approximations provided a specific DD.…”