Geographic distribution and relative abundance of the invasive glassy-winged sharpshooter: effects of temperature and egg parasitoids

Insecticidal Effect of Entomopathogenic Nematodes and the Cell-Free Supernatant from Their Symbiotic Bacteria against Philaenus spumarius (Hemiptera: Aphrophoridae) Nymphs

The meadow spittlebug Philaenus spumarius (Hemiptera: Aphrophoridae) is the primary vector of Xylella fastidiosa (Proteobacteria: Xanthomonadaceae) in Europe, a pest-disease complex of economically relevant crops such as olives, almonds, and grapevine, managed mainly through the use of broad-spectrum pesticides. Providing environmentally sound alternatives to reduce the reliance on chemical control is a primary challenge in the control of P. spumarius and, hence, in the protection of crops against the expansion of its associated bacterial pathogen. Entomopathogenic nematodes (EPNs) are well-known biocontrol agents of soil-dwelling arthropods. Recent technological advances in field applications, including improvements in obtaining cell-free supernatant from their symbiotic bacteria, allow their successful implementation against aerial pests. Thus, this study aimed to evaluate, for the first time, the efficacy of EPN applications against nymphal instars of P. spumarius. We tested four EPN species and the cell-free supernatant of their corresponding symbiotic bacteria: Steinernema feltiae-Xenorhabdus bovienii, S. carpocapsae-X. nematophila, S. riojaense-X. kozodoii, and Heterorhabditis bacteriophora-Photorhabdus laumondii subsp. laumondii. First, we showed that 24 and 72 h exposure to the foam produced by P. spumarius nymphs did not affect S. feltiae virulence. The direct application of steinernematid EPNs provided promising results, reaching 90, 78, and 53% nymphal mortality rates after five days of exposure for S. carpocapsae, S. feltiae, and S. riojaense, respectively. Conversely, the application of the cell-free supernatant from P. laumondii resulted in nymphal mortalities of 64%, significantly higher than observed for Xenorhabdus species after five days of exposure. Overall, we demonstrated the great potential of the application of specific EPNs and cell-free supernatant of their symbiont bacteria against P. spumarius nymphs, introducing new opportunities to develop them as biopesticides for integrated management practices or organic vineyard production.

Models Applied to Grapevine Pests: A Review

Simple Summary

Mathematical models are developed to predict key aspects of insects harmful to many crops, including grapevine. Practical applications of these models include forecasting seasonal occurrence and spread over space in order to make decisions about pest management (e.g., timing of insecticide sprays). Many models have recently been developed to evaluate the spread of insect pests on grapevine under a climate change scenario as well as to forecast the possibility that alien species could settle into new environments. To make the published models available to vine-growers and their stakeholders, a holistic approach presenting these models within the frame of a decision support system should be followed.

Abstract

This paper reviews the existing predictive models concerning insects and mites harmful to grapevine. A brief conceptual description is given on the definition of a model and about different types of models: deterministic vs. stochastics, continuous vs. discrete, analytical vs. computer-based, and descriptive vs. data-driven. The main biological aspects of grapevine pests covered by different types of models are phenology, population growth and dynamics, species distribution, and invasion risk. A particular emphasis is put on forecasting epidemics of plant disease agents transmitted by insects with sucking-piercing mouthparts. The most investigated species or groups are the glassy-winged sharpshooter Homalodisca vitripennis (Germar) and other vectors of Xylella fastidiosa subsp. fastidiosa, a bacterium agent of Pierce’s disease; the European grape berry moth, Lobesia botrana (Denis and Schiffermuller); and the leafhopper Scaphoideus titanus Ball, the main vector of phytoplasmas agents of Flavescence dorée. Finally, the present and future of decision-support systems (DSS) in viticulture is discussed.

Small world in the real world: Long distance dispersal governs epidemic dynamics in agricultural landscapes

Outbreaks of a plant disease in a landscape can be meaningfully modelled using networks with nodes representing individual crop-fields, and edges representing potential infection pathways between them. Their spatial structure, which resembles that of a regular lattice, makes such networks fairly robust against epidemics. Yet, it is well-known how the addition of a few shortcuts can turn robust regular lattices into vulnerable 'small world' networks. Although the relevance of this phenomenon has been shown theoretically for networks with nodes corresponding to individual host plants, its real-world implications at a larger scale (i.e. in networks with nodes representing crop fields or other plantations) remain elusive. Focusing on realistic spatial networks connecting olive orchards in Andalusia (Southern Spain), the world's leading olive producer, we show how even very small probabilities of long distance dispersal of infectious vectors result in a small-world effect that dramatically exacerbates a hypothetical outbreak of a disease targeting olive trees (loosely modelled on known epidemiological information on the bacterium Xylella fastidiosa, an important emerging threat for European agriculture). More specifically, we found that the probability of long distance vector dispersal has a disproportionately larger effect on epidemic dynamics compared to pathogen's intrinsic infectivity, increasing total infected area by up to one order of magnitude (in the absence of quarantine). Furthermore, even a very small probability of long distance dispersal increased the effort needed to halt a hypothetical outbreak through quarantine by about 50% in respect to scenarios modelling local/short distance pathogen's dispersal only. This highlights how identifying (and disrupting) long distance dispersal processes may be more efficacious to contain a plant disease epidemic than surveillance and intervention concentrated on local scale transmission processes.

Xylella fastidiosa: bacterial parasitism with hallmarks of commensalism

All organisms evolve in the presence of other organisms and these intimate associations are major drivers of evolution. Broadly speaking, these interactions are considered symbioses and can take on a full range of positive, negative or seemingly neutral interactions. Just two examples of these symbiotic interactions are parasitism and commensalism. Parasitism results in one partner benefitting while one partner suffers adverse consequences. Commensalism is a form of symbiosis where one partner benefits and the other partner is neutrally affected. Research efforts are more often focused on understanding parasitic symbioses related to disease, hence, much research is performed on identifying virulence factors to understand the fundamentals of pathogenesis. In turn, much less is understood about the fundamentals of commensal relationships. Here, we will take an introspective look at the plant-associated bacterium, Xylella fastidiosa. In some of its many plant hosts, this bacterium participates in seemingly commensal relationships while in other hosts, it causes devastating diseases that result in epidemics, making it a good model for exploring the determinants of where bacteria fall on the spectrum of parasitic and commensal relationships from both the microbial and the plant host perspective. Recent discoveries in how pathogenic X. fastidiosa imposes self-limiting behaviors upon itself indicate that even in its parasitic form, X. fastidiosa displays hallmarks of a commensal lifestyle. Understanding how commensalism can 'go wrong' and manifest into pathologies in specific hosts is a useful vantage point from which to study the determinants of virulence and pathogenicity.

Development and validation of a real-time PCR assay for the glassy-winged sharpshooter Homalodisca vitripennis (Hemiptera: Cicadellidae)

The glassy-winged sharpshooter (Homalodisca vitripennis) is an invasive pest organism, which is found throughout Central America and has recently invaded a few countries in the Pacific Islands. As a carrier of the highly virulent plant pathogenic bacterium Xylella fastidiosa, it is of great economic significance to horticulture and is estimated to cost Californian vineyards over US$100 million per year in control and losses. New Zealand is currently free from this pest, but its recent spread through the Pacific has raised concerns of it establishing in New Zealand, potentially as a result of introduction through human travel. We report here a real-time polymerase chain reaction assay for the rapid identification of H. vitripennis. The assay was extensively validated in silico then optimized and tested against a range of Cicadellidae species, both internationally collected and local to New Zealand. This assay was able to correctly identify H. vitripennis samples, and distinguish between H. vitripennis and close relatives, such as the smoke-tree sharpshooter (Homalodisca liturata) and will be of great benefit to New Zealand biosecurity.

Developmental models for estimating ecological responses to environmental variability: structural, parametric, and experimental issues

Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

Eradication of invasive species: why the biology matters

Published bi- and tri-trophic physiologically based demographic system models having similar sub components are used to assess prospectively the geographic distributions and relative abundance (a measure of invasiveness) of six invasive herbivorous insect species across the United States and Mexico. The plant hosts and insect species included in the study are: 1) cotton/pink bollworm, 2) a fruit tree host/Mediterranean fruit fly, 3) olive/olive fly, 4) a perennial host/light brown apple moth, 5) grapevine/glassy-winged sharpshooter and its two egg parasitoids, and 6) grapevine/European grapevine moth. All of these species are currently or have been targets for eradication. The goal of the analyses is to predict and explain prospectively the disparate distributions of the six species as a basis for examining eradication or containment efforts against them. The eradication of the new world screwworm is also reviewed in the discussion section because of its pivotal role in the development of the eradication paradigm. The models used are mechanistic descriptions of the weather driven biology of the species. Observed daily weather data (i.e., max-min temperatures, solar radiation) from 1,221 locations across the United States and Mexico for the period 1983-2003 were used to drive the models. Soil moisture and nutrition were assumed nonlimiting. The simulation results were mapped using GRASS GIS. The mathematical underpinnings of the modeling approach are reviewed in the appendix and in the supplemental materials.