A modelling framework for pest population dynamics and management: An application to the grape berry moth

A model for predicting the phenology of Philaenus spumarius

The design and implementation of Philaenus spumarius control strategies can take advantage of properly calibrated models describing and predicting the phenology of vector populations in agroecosystems. We developed a temperature-driven physiological-based model based on the system of Kolmogorov partial differential equations to predict the phenological dynamics of P. spumarius. The model considers the initial physiological age distribution of eggs, the diapause termination process, and the development rate functions of post-diapausing eggs and nymphal stages, estimated from data collected in laboratory experiments and field surveys in Italy. The temperature threshold and cumulative degree days for egg diapause termination were estimated as 6.5 °C and 120 DD, respectively. Preimaginal development rate functions exhibited lower thresholds ranging between 2.1 and 5.0 °C, optimal temperatures between 26.6 and 28.3 °C, and upper threshold between 33.0 and 35 °C. The model correctly simulates the emergence of the 3rd, 4th, and 5th nymphal instars, key stages to target monitoring actions and control measures against P. spumarius. Precision in simulating the phenology of the 1st and 2nd nymphal stages was less satisfactory. The model is a useful rational decision tool to support scheduling monitoring and control actions against the late and most important nymphal stages of P. spumarius.

Temperature sensitivity of pest reproductive numbers in age-structured PDE models, with a focus on the invasive spotted lanternfly

Invasive pest establishment is a pervasive threat to global ecosystems, agriculture, and public health. The recent establishment of the invasive spotted lanternfly in the northeastern United States has proven devastating to farms and vineyards, necessitating urgent development of population dynamical models and effective control practices. In this paper, we propose a stage-age-structured system of PDEs to model insect pest populations, in which underlying dynamics are dictated by ambient temperature through rates of development, fecundity, and mortality. The model incorporates diapause and non-diapause pathways, and is calibrated to experimental and field data on the spotted lanternfly. We develop a novel moving mesh method for capturing age-advection accurately, even for coarse discretization parameters. We define a one-year reproductive number ([Formula: see text]) from the spectrum of a one-year solution operator, and study its sensitivity to variations in the mean and amplitude of the annual temperature profile. We quantify assumptions sufficient to give rise to the low-rank structure of the solution operator characteristic of part of the parameter domain. We discuss establishment potential as it results from the pairing of a favorable [Formula: see text] value and transient population survival, and address implications for pest control strategies.

Non-linear physiological responses to climate change: the case of Ceratitis capitata distribution and abundance in Europe

Understanding how climate change might influence the distribution and abundance of crop pests is fundamental for the development and the implementation of pest management strategies. Here we present and apply a modelling framework assessing the non-linear physiological responses of the life-history strategies of the Mediterranean fruit fly (Ceratitis capitata, Wiedemann) to temperature. The model is used to explore how climate change might influence the distribution and abundance of this pest in Europe. We estimated the change in the distribution, abundance and activity of this species under current (year 2020) and future (years 2030 and 2050) climatic scenarios. The effects of climate change on the distribution, abundance and activity of C. capitata are heterogeneous both in time and in space. A northward expansion of the species, an increase in the altitudinal limit marking the presence of the species, and an overall increase in population abundance is expected in areas that might become more suitable under a changing climate. On the contrary, stable or reduced population abundances can be expected in areas where climate change leads to equally suitable or less suitable conditions. This heterogeneity reflects the contribution of both spatial variability in the predicted climatic patterns and non-linearity in the responses of the species’ life-history strategies to temperature.

A nonlinear model for stage-structured population dynamics with nonlocal density-dependent regulation: An application to the fall armyworm moth

The assessment and the management of the risks linked to insect pests can be supported by the use of physiologically-based demographic models. These models are useful in population ecology to simulate the dynamics of stage-structured populations, by means of functions (e.g., development, mortality and fecundity rate functions) realistically representing the nonlinear individuals physiological responses to environmental forcing variables. Since density-dependent responses are important regulating factors in population dynamics, we propose a nonlinear physiologically-based Kolmogorov model describing the dynamics of a stage-structured population in which a time-dependent mortality rate is coupled with a nonlocal density-dependent term. We prove existence and uniqueness of the solution for this resulting highly nonlinear partial differential equation. Then, the equation is discretized by finite volumes in space and semi-implicit backward Euler scheme in time. The model is applied for simulating the population dynamics of the fall armyworm moth (Spodoptera frugiperda), a highly invasive pest threatening agriculture worldwide.

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.

Pest Management and Ochratoxin A Contamination in Grapes: A Review

Ochratoxin A (OTA) is the most toxic member of ochratoxins, a group of toxic secondary metabolites produced by fungi. The most relevant species involved in OTA production in grapes is Aspergillus carbonarius. Berry infection by A. carbonarius is enhanced by damage to the skin caused by abiotic and biotic factors. Insect pests play a major role in European vineyards, and Lepidopteran species such as the European grapevine moth Lobesia botrana are undoubtedly crucial. New scenarios are also emerging due to the introduction and spread of allochthonous pests as well as climate change. Such pests may be involved in the dissemination of OTA producing fungi even if confirmation is still lacking and further studies are needed. An OTA predicting model is available, but it should be integrated with models aimed at forecasting L. botrana phenology and demography in order to improve model reliability.

Development and calibration of a model for the potential establishment and impact of Aedes albopictus in Europe

The Asian tiger mosquito (Aedes albopictus) is one of the most invasive disease vectors worldwide. The species is a competent vector of dengue, chikungunya, Zika viruses and other severe parasites and pathogens threatening human health. The capacity of this mosquito to colonize and establish in new areas (including temperate regions) is enhanced by its ability of producing diapausing eggs that survive relatively cold winters. The main drivers of population dynamics for this mosquito are water and air temperature and photoperiod. In this paper, we present a mechanistic model that predicts the potential distribution, abundance and activity of Asian tiger mosquito in Europe. The model includes a comprehensive description of: i) the individual life-history strategies, including diapause, ii) the influence of weather-driven individual physiological responses on population dynamics and iii) the density-dependent regulation of larval mortality rate. The model is calibrated using field data from several locations along an altitudinal gradient in the Italian Alps, which enabled accurate prediction of cold temperature effects on population abundance, including identification of conditions that prevent overwintering of the species. Model predictions are consistent with the most updated information on species' presence and absence. Predicted population abundance shows a clear south-north decreasing gradient. A similar yet less evident pattern in the activity of the species is also predicted. The model represents a valuable tool for the development of strategies aimed at the management of Ae. albopictus and for the implementation of effective control measures against vector-borne diseases in Europe.

Critical Success Factors for the Adoption of Decision Tools in IPM

The rational control of harmful organisms for plants (pests) forms the basis of the integrated pest management (IPM), and is fundamental for ensuring agricultural productivity while maintaining economic and environmental sustainability. The high level of complexity of the decision processes linked to IPM requires careful evaluations, both economic and environmental, considering benefits and costs associated with a management action. Plant protection models and other decision tools (DTs) have assumed a key role in supporting decision-making process in pest management. The advantages of using DTs in IPM are linked to their capacity to process and analyze complex information and to provide outputs supporting the decision-making process. Nowadays, several DTs have been developed, tackling different issues, and have been applied in different climatic conditions and agricultural contexts. However, their use in crop management is restricted to only certain areas and/or to a limited group of users. In this paper, we review the current state-of-the-art related to DTs for IPM, investigate the main modelling approaches used, and the different fields of application. We also identify key drivers influencing their adoption and provide a set of critical success factors to guide the development and facilitate the adoption of DTs in crop protection.

Pest management under climate change: The importance of understanding tritrophic relations

Plants and insects depend on climatic factors (temperature, solar radiation, precipitations, relative humidity and CO₂) for their development. Current knowledge suggests that climate change can alter plants and insects development and affect their interactions. Shifts in tritrophic relations are of particular concern for Integrated Pest Management (IPM), because responses at the highest trophic level (natural enemies) are highly sensitive to warmer temperature. It is expected that natural enemies could benefit from better conditions for their development in northern latitudes and IPM could be facilitated by a longer period of overlap. This may not be the case in southern latitudes, where climate could become too warm. Adapting IPM to future climatic conditions requires therefore understanding of changes that occur at the various levels and their linkages. The aim of this review is to assess the current state of knowledge and highlights the gaps in the existing literature concerning how climate change can affect tritrophic relations. Because of the economic importance of wine production, the interactions between grapevine, Vitis vinifera (1st), Lobesia botrana (2nd) and Trichogramma spp., (3rd), an egg parasitoid of Lobesia botrana, are considered as a case study for addressing specific issues. In addition, we discuss models that could be applied in order quantify alterations in the synchrony or asynchrony patterns but also the shifts in the timing and spatial distribution of hosts, pests and their natural enemies.

A temperature-dependent physiologically based model for the invasive apple snail Pomacea canaliculata

In order to set priorities in management of costly and ecosystem-damaging species, policymakers and managers need accurate predictions not only about where a specific invader may establish but also about its potential abundance at different geographical scales. This is because density or biomass per unit area of an invasive species is a key predictor of the magnitude of environmental and economic impact in the invaded habitat. Here, we present a physiologically based demographic model describing and explaining the population dynamics of a widespread freshwater invader, the golden apple snail Pomacea canaliculata, which is causing severe environmental and economic impacts in invaded wetlands and rice fields in Southeastern Asia and has also been introduced to North America and Europe. The model is based on bio-demographic functions for mortality, development and fecundity rates that are driven by water temperature for the aquatic stages (juveniles and adults) and by air temperature for the aerial egg masses. Our model has been validated against data on the current distribution in South America and Japan, and produced consistent and realistic patterns of reproduction, growth, maturation and mortality under different scenarios in accordance to what is known from real P. canaliculata populations in different regions and climates. The model further shows that P. canaliculata will use two different reproductive strategies (semelparity and iteroparity) within the potential area of establishment, a plasticity that may explain the high invasiveness of this species across a wide range of habitats with different climates. Our results also suggest that densities, and thus the magnitude of environmental and agricultural damage, will be largely different in locations with distinct climatic regimes within the potential area of establishment. We suggest that physiologically based demographic modelling of invasive species will become a valuable tool for invasive species managers.

Mortality of Eggs and Newly Hatched Larvae of Lobesia botrana (Lepidoptera: Tortricidae) Exposed to High Temperatures in the Laboratory

The hypothesis that bunch-zone leaf removal reduces infestations of the European grapevine moth, Lobesia botrana (Denis & Schiffermüller) (Lepidoptera: Tortricidae), by increasing egg and larval mortality owing to sunlight exposure was evaluated in the laboratory by subjecting different egg stages (white, red-eyes, and black-head) and newly hatched larvae to high temperatures. Based on temperatures recorded in a northern Italian vineyard on sun-exposed berries belonging to south-west facing bunches, eggs were subjected to constant temperatures of 40 °C and 37 °C for one or two periods of 3 or 6 h, and to 24-h temperature cycle with peak of 40 °C. Larvae were exposed to 24-h high-temperature cycles with peaks of 35, 37, and 40 °C. The results showed partial egg mortality at 40 °C, increasing with exposure hours and periods, and as eggs matured. Egg mortality was not affected by exposure to 37 °C. Larval survival already decreased significantly at 37 °C and was even lower at 40 °C. These laboratory data are in agreement with the hypothesis that temperatures reached by berries exposed to sunlight cause egg and larval mortality. Data on egg and larval susceptibility to high temperatures have also implications for species distribution and effects of climate change.

A Bayesian estimation approach for the mortality in a stage-structured demographic model

Control interventions in sustainable pest management schemes are set according to the phenology and the population abundance of the pests. This information can be obtained using suitable mathematical models that describe the population dynamics based on individual life history responses to environmental conditions and resource availability. These responses are described by development, fecundity and survival rate functions, which can be estimated from laboratory experiments. If experimental data are not available, data on field population dynamics can be used for their estimation. This is the case of the extrinsic mortality term that appears in the mortality rate function due to biotic factors. We propose a Bayesian approach to estimate the probability density functions of the parameters in the extrinsic mortality rate function, starting from data on population abundance. The method investigates the time variability in the mortality parameters by comparing simulated and observed trajectories. The grape berry moth, a pest of great importance in European vineyards, has been considered as a case study. Simulated data have been considered to evaluate the convergence of the algorithm, while field data have been used to obtain estimates of the mortality for the grape berry moth.

Spatial and Host-Related Variation in Prevalence and Population Density of Wheat Curl Mite (Aceria tosichella) Cryptic Genotypes in Agricultural Landscapes

The wheat curl mite (WCM), Aceria tosichella Keifer, is a major pest of cereals worldwide that also comprises a complex of at least 16 genetic lineages with divergent physiological traits, including host associations and specificity. The goal of this study was to test the extent to which host-plant species and landscape spatial variation influence WCM presence and population density across the entire area of Poland (>311,000 km2). Three important findings arose from the results of the study. (1) The majority of WCM lineages analyzed exhibited variation in patterns of prevalence and/or population density on both spatial and host-associated scales. (2) Areas of occurrence and local abundance were delineated for specific WCM lineages and it was determined that the most pestiferous lineages are much less widespread than was expected, suggesting relatively recent introductions into Poland and the potential for further spread. (3) The 16 WCM lineages under study assorted within four discrete host assemblages, within which similar host preferences and host infestation patterns were detected. Of these four groups, one consists of lineages associated with cereals. In addition to improving basic ecological knowledge of a widespread arthropod herbivore, the results of this research identify high-risk areas for the presence of the most pestiferous WCM lineages in the study area (viz. the entirety of Poland). They also provide insight into the evolution of pest species of domesticated crops and facilitate testing of fundamental hypotheses about the ecological factors that shape this pest community.