Egg Hatching and First Instar Falling Models of Metcalfa pruinosa (Hemiptera: Flatidae)

Predicting suitable areas for Metcalfa pruinosa (Hemiptera: Flatidae) under climate change and implications for management

Climate change is a prominent factor reshaping the distribution of invasive species. Metcalfa pruinosa (Say 1830) (Hemiptera: Flatidae), native to North America, has invaded other continents and poses a serious threat to various agricultural crops and the human residential environment. Understanding the distribution of M. pruinosa based on climatic conditions is a critical first step to prevent its further invasion. Therefore, based on its occurrence records and associated environmental variables, a Maxent model was developed to predict suitable areas for this species in the present and future on a global scale. The model exhibited outstanding performance, with a mean area under the receiver operating characteristic curve and true skill statistic values of 0.9329 and 0.926, respectively. The model also indicated that annual precipitation (Bio12) and max temperature of the warmest month (Bio5) were the key environmental variables limiting the distribution of M. pruinosa. Moreover, the model revealed that the current suitable area is 1.01 × 107 km2 worldwide, with southern China, southern Europe, and the eastern United States predicted to be the primary and highly suitable areas in the latter 2 regions. This area is expected to increase under future climate scenarios, mainly in the northern direction. The study's findings contribute to our understanding of climate change's impact on M. pruinosa distribution, and they will aid governments in developing appropriate pest management strategies, including global monitoring and strict quarantine measures.

Phenology model development for Neodryinus typhlocybae: Evaluation of phenological synchrony with its host, Metcalfa pruinosa

The invasive species Metcalfa pruinosa has inflicted significant economic losses in various European and Asian regions. To combat this pest, the parasitoid wasp Neodryinus typhlocybae has been effectively introduced in Europe. Despite its success, research on the field occurrence patterns of N. typhlocybae, particularly its phenology, remains scarce. This study aims to develop a degree-day model for predicting the adult emergence of N. typhlocybae from overwintering cocoons and to assess the phenological synchrony between N. typhlocybae adults and the nymphal stages of M. pruinosa in Korea. In this study, we estimated the thermal parameters of N. typhlocybae under field temperatures and six constant temperatures (13.92, 17.71, 18.53, 20.53, 22.78, and 24.03 °C) conditions. The lower developmental temperature was estimated using the values of the coefficient of variation for the cumulative degree days of emerged individual adults. The estimated lower developmental threshold temperature was 12.3 °C. With this developmental threshold, a degree-day model was developed, and this model well-predicted emergence in field conditions. By simulating this developed model with the actual occurrence of the nymphal stages of its host, M. pruinosa, adult wasp emergence was estimated to be 1.5 weeks later than the first instar nymph of the host but faster than other nymphal stages of M. pruinosa. Thus, the findings in this study would be helpful in determining the possibility of establishing N. typhlocybae and improving the management efficiency of M. pruinosa.

Degree-day-based model to predict egg hatching of Philaenus spumarius (Hemiptera: Aphrophoridae), the main vector of Xylella fastidiosa in Europe

Philaenus spumarius L., the main vector of Xylella fastidiosa (Wells) in Europe, is a univoltine species that overwinters in the egg stage, and its nymphs emerge in late winter or spring. Predicting the time of egg hatching is essential for determining the precise times for deploying control strategies against insect pests. Here, we monitored P. spumarius eggs from oviposition to egg hatching together with the daily temperatures and relative humidities at four field locations that were located at different altitudes in central Spain. The collected data were used to build a growing degree day (GDD) model to forecast egg hatching in the Iberian Peninsula. Furthermore, the model was validated with field observations that were conducted in Spain. The model was then used as a decision-support tool to calculate the optimum timing for applying control actions against P. spumarius. Our results suggest that controlling nymphs at two different dates would target the highest percentages of nymphal populations present in the field. Our model represents a first step for predicting the emergence of nymphs and adopting timely control actions against P. spumarius. These actions could limit disease spread in areas where X. fastidiosa is present.

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.